COVID-19: Data collection and transparency among countries

This chapter discusses the importance of data collection and transparency as two important topics closely related with strong impact in the appropriate management of an epidemiological emergency like coronavirus disease 2019 pandemic. Based on the lessons learned, a centralized organization should collect few but substantial data that could be used for global and local decisions. In addition, local laws and policies related to transparency should be considered and approved by governments in order to develop trust in the public opinion.

Introduction
The coronavirus disease 2019 (COVID- 19) pandemic is a public health problem with extensive implications for health systems and economies around the globe. The first cases were reported as a pneumonia of unknown origin in Wuhan, China, on December 31, 2019. 1 The World Health Organization (WHO) announced through social media outlets about these cases during the first week of January, and in the same week, the agent was identified as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 2 This new coronavirus showed immediately the attribute to spread efficiently to new countries and regions outside China, such as Philippines, France, Italy, Spain, and the United States.
It is important to note that the first data was collected and analyzed by local Chinese authorities where the outbreak was taking place, and the timing that took identifying the first case to the moment that they shared the information with WHO was reported as immediate, a claim that was not challenged in the first phase of the pandemic. Another interesting fact is that, in the very beginning, WHO or the scientific community did not have any doubt about the authenticity of the data being shared by Chinese officials. The data began to flow through the weekly WHO bulletins, and later, the Johns Hopkins University (JHU) developed the Coronavirus Resource Center that kept track of the coronavirus cases based largely on data provided by 188 different countries and regions of the world. 3 As the pandemic developed, most individuals turned to the JHU resource to have a timely and reliable data of the COVID-19 cases. As of the preparation of this chapter, this resource has been the most popular (even more popular that the official site of WHO for COVID-19 4 ), despite the fact that a few actually know where the data for its dashboard comes from, and even less, take the time to verify the authenticity of the source of the data used for this information, which includes media reports. For a while, this information was not challenged, but as the dynamic of the pandemic developed, questions arose about the data that were collected and about the information provided after the analysis of such data. Here is where the issue of transparency emerged, especially triggered by the reports that questioned the information provided by Chinese officials in regard to the start of the pandemic. At the same time, similar concerns were raised in other high-income countries, 5 including lower middle-income countries like Guatemala, that challenged the transparency of the data and information presented by local authorities.
With this chapter, we want the reader to have a brief overview, from the perspective of a clinical epidemiologist, of the lessons learned on two key epidemiological aspects in the process to inform authorities and society related to COVID-19 being those: (1) data collection and (2) transparency in the data.

Lessons learned about COVID-19 data collection
The WHO is the leading institution when it comes to data and information related to an epidemiological emergency. 6 For the purposes of this chapter, it is important to understand that WHO's key role is to coordinate data collection and provides information based on analysis of the data in a global context. Based on this information, technical and financial support is provided to countries around the globe. Of utmost importance is to note that WHO monitors constantly the data and information that is provided by the different countries and regions of the world. 7 Also, interesting to note is that collecting the data in a dynamic global context is both a strength and a weakness, because what WHO gains from obtaining data of authorities, losses in the quality of the data that is provided by Ministries of Health, that respond directly to the highest authorities in government who decide which data and when the data is released, something that is of key importance when making decisions in the midst of an epidemiological emergency, as the current COVID-19 pandemic.
During the first days of the COVID-19 pandemic, there were no questions, at least in the general public, about the data and information that was provided through WHO bulletins or the JHU site, especially the ones that came from China. Then, as the virus spread around the globe, data from France, Italy, Spain, and the United States emerged, and in a similar manner, there were no questions about the data and information. But things began to change as the pandemic evolved, and questions began to raise in regard to the data and information provided by China, after the concerns that were expressed by the highest authorities in the United States government.
As a response, China issued a statement which confirmed that they have followed the protocols and processes required by WHO in matters pertaining to data collection and reporting, making emphasis that they have complied with all these standards based on international agreements, in a timely manner. We must draw the attention that at this point, there were no questions from WHO or other key institutions leading to believe that the data collection and analysis provided by China or any other government around the world were flawed. However, the media and news outlets, through investigative journalist methods, 8 inquired about the authenticity of the data provided by governments and centered their attention in the question of hidden data. The investigations lead to findings such as that the first case could have been in the mid of November 2019. 9 In addition, independent investigators from Harvard University conducted a study based on satellite pictures and online searches around the Wuhan area and reported that the first cases could have happened as early as August 2019 10 . Through these findings, we have learned two important lessons which are: first, media and news outlets play a key role in creating questions for the public opinion about the way data are obtained and how this information is communicated, and second, the importance of trust in local and global authorities about the transparency in management of data collection and generation of information, as it is mentioned in WHO fundamental guidelines on how to collect data during epidemiological emergencies.

Lessons learned about COVID-19 data transparency
Transparent is defined as being "free from pretense or deceit", 11 and it is expected that by all means, a government is committed to be obedient to the law, and even more, comply with high ethical standards in the way that manage data and communicate information to increase the benefits for the general public and avoid risk that could harm their lives. This, in short, should be the main aspects that any government should follow, so the mitigation directions issued are followed by society and in that way prevent the impact and high cost in morbidity and mortality of vulnerable populations during an epidemiological emergency.
So far, COVID-19 pandemic has been a challenge in regard to empower governments to lead the actions that could mitigate the impact of this virus in their countries. China, being a high-income country, has been questioned about the transparency of the data and information that provided to the world. 12 One of the errors they have made was the decision to control and limit the scientific information that was requested by the scientific communities 13 to understand better how SARS-CoV-2 appeared and behaved. No information could be provided without government authorization. That simple decision created a distrust in what was reported by Chinese institutions, something that has remained to date and could take time to overcome. Therefore the sole reaction of limiting the information was perhaps one of the most damaging actions of the Chinese government, and the worst part is that the media was not the only one reporting the lack of transparency from the Chinese government but also the scientific networks around the world raised their concern that Chinese scientists were coerced to not to share their data and information and even seek collaborations with scientists who wanted to understand better COVID-19 as the SARS-CoV-2 was spreading to other countries.
Unfortunately, similar attitudes were shown governments of lower middleincome countries, like Guatemala where the first case was reported on March 13. During the first month, the information provided by the Ministry of Health was openly received by media outlets, population, and scientific community, and in short, no questions were made as of the reliability and timely manner that this was received. However, as the pandemic developed, the scientific community and society had concerns about the number of COVID-19 tests that were performed. Certainly, the acquisition of tests was a very difficult and important issue to address, from the government perspective, and even more challenging was to communicate to the general public about the lack of tests around the globe 14 . Among the general public, it is a common belief that a test has been validated by the time that a pandemic starts, and just a few could understand that such is not the case in certain epidemiological emergencies as was the case for SARS-CoV-2. Societies believe that funding is enough to secure a test, and in certain way it does, but with SARS-CoV-2, the issue of having funds did not secure the possibility of having a reliable test in which the health systems could trust to identify the cases among the general population. Therefore, there was a key communication issue that needed to be addressed, which was to explain the relation that has the availability of a test and the possibility to confirm a case (no test, no data), which limits the possibility to understand how a highly infectious disease behaves from the beginning.
Another situation that happened in Guatemala was the presidential daily briefing that presented to the public the COVID-19 information. The format of such briefings was inconsistent, and there was a lack of clarity for the general public. Therefore, the Guatemalan population did not completely understand the data and even noticed when contradicted data was presented to them. Based on that, as in China, news outlets 15 in Guatemala began to search deeply into the information 16 and finally, the government acknowledged that there was a sub-registry in the data that they were providing during the briefing and error not directly related to the lack of tests, but of information that was not transferred to them, especially, in regard to the number of deaths occurring in Guatemala. What should be considered as simple situation turned out to be a key issue that has been the center of what is considered as the main driver of the lack of success in the mitigation measures implemented by the government, which was the perception of lack of transparency and fear of corruption that was reported in the media, 17 and eventually, this ended up in the distrust on government planning and decisions, which lead to an increased number of COVID-19 cases, something that has been the trend to the day that this chapter was written.

What could be implemented to improve data collection for COVID-19
If data collection is a fundamental aspect that must be defined in the beginning of an epidemiological emergency, then it is important that Ministries of Health, as the highest authorities, must clearly define the procedures that not only locally but also globally must govern the data collection and subsequent storage and analysis to provide timely and reliable information. One main limitation that exists around the globe is that there is not a universal validated tool that could be used and applied in local and international contexts to collect data with the purpose of informing in a timely manner of the cases who are identified during an epidemic crisis.
There have been efforts to develop such tools, but the initiatives have moved only to the stage of a proposal, never becoming a universal tool that could be used by Ministries of Health. There could be many reasons that could explain why the implementation of such tools might be challenging. First, there are "political" reasons, which usually are more economical reasons, that intentionally avoid to create a collaborative environment. It has been well established that when a country faces an epidemiological emergency, the economic impact becomes the highest priority relegating the provision of adequate health services to a last place. In many ways, COVID-19 is teaching us that prioritizing the economic factors over the health will eventually lead to a more complex health problem. Hiding the data from the international scientific community, and not giving time to carefully analyze it, will eventually create a situation that will affect not only the country that was primarily affected but also the globe to a point that even commerce could stagger and deepen the economic inequalities. 18 Governments, and specifically Ministries of Health, must carefully begin to outline clear policies and plans that will guide actions during such epidemiological emergencies, and the first public health policy in epidemiological emergencies should be the one about data collecting and sharing with the international community and the general public. 19 Technical teams at Ministries of Health must know that if there is a need to share data, an important issue should be what data must be collected. That takes us again to the universal tool that we have mentioned before. The tool selected must be developed in consensus with other governments, and a guideline with a clear process must be prepared to be used in epidemiological emergencies. It will be expected that such guidelines should be developed in consultation with the WHO, and a clear statement should be made within the United Nations in order to adopt such tool in a universal manner. There are immediate limitations in this proposal, mainly due to political distinctions among countries and regions, especially between world potencies, that ultimately have the possibility to vote and decide if they will adopt the tool and share this data in the areas where they exercise an economical and military influence (we must keep present that an epidemiological emergency as the SARS-CoV-2 pandemic is considered a national security concern for world potencies). Undoubtedly, there is a primary institution that should promote the development of such a tool and that should be the WHO; however, if we argue that today's pandemics have a heavy impact in international commerce, then another instance that should be considered to coordinate these efforts is the World Trade Organization (WTO). This second option should not be a surprise, 20 because we have argued before that at the beginning of a pandemic, the priorities of governments are usually commerce over health, and COVID-19 clearly has become a commerce problem with local and international implications.
Once the world has consented the organization from where this tool will be developed, then it is important to define what kind of data should be collected. This again should not be a difficult issue to define. A common mistake of Ministries of Health is trying to collect a vast amount of data that ends up in large quantities of bytes stored in some electronic device that is never analyzed. But this should change. As mentioned earlier, of key importance is to be able to accurately count the cases. COVID-19 was difficult in the aspect that there was no diagnosis test available, and once this was developed, such test was inaccessible for two reasons. First, because the technologies used to identify the antigen usually requires highly trained human resources and specialized equipment that is not easily available, especially in lower middle-income countries. Second, once the technology has been developed, there is the possibility that patents and licenses for such technologies are too expansive, that acquisition becomes prohibitive for countries that do not have the means to fund immediately the acquisition of such tests. This directly impacts the possibility to have accurate data (remember: no test, no data) that could be reported in a local and global context. Therefore every effort should be made toward obtaining and having the possibility to have availability and accessibility to a diagnosis test that could be applied globally, regardless of being in a high-, middle-, or lower-income country. Certainly, an economy based on free market will challenge this proposal; nevertheless, COVID-19 is teaching us that in a context where a pandemic exists in the free market around the world will be as strong as the weakest of the countries.
One important aspect also is to define the data that should be collected. 21 It is possible that the first data that must be collected will be the cases confirmed by an accurate diagnostic test. The second data that should be obtained is the swabs performed. 22 Interestingly, most of the countries report the number of positive cases per day; however, this might be accurate for high-income countries where there is the technology readily available and in a short amount of time the results are available, but it is difficult to find such situations in a lower middle-income countries. Guatemala's experience was that in some cases it took 8 days to report the test result. So, the fact that this was presented as positive in a given date, which did not reflect the exact moment of when the case was happening, giving an inaccurate picture of the situation in real time. 23 Is in that regard that it would be preferable to report the number of positive cases based on the daily swabs than the daily performed diagnosis.
The third data will be the number of deaths related to COVID-19, which is another important and challenging data that must be collected and reported. The challenge of this data is that it also needs to have a positive test for the diagnosis; however, it would be even better if the death could be also confirmed with an autopsy. But, the fact that most health services lack a test at the beginning of the pandemic, and it is not readily available for a long time, as previously stated, it might be difficult for countries to have a positive test on one end. On the other end, most health services, once the patient dies, immediately proceed to bury the cadaver without an autopsy. The lack of an autopsy limits the possibility to better understand the viral action in all the systems that comprise the human body. What would be better and should be suggested, is to conduct autopsies of the cases 24 and report the number of autopsies that finally confirms that the death was directly related to COVID-19. 25 Other mandatory data must be collected, like demographic data from the patient, length of hospitalization, etc. These suggestions of data that could be collected have the potential to inform more than a vast number of pages with information that none reads or finds practical use in order to inform decisions at all levels of public health and clinical settings.
In a global context, it would be suggested to have few data that could be shared immediately to a central organization that could collect timely and reliable data from all Ministries of Health around the world and have an accurate image of the global situation in a given epidemiological emergency.
What could be implemented to improve data transparency for COVID-19 Given the sensitive nature of the data and information that is generated during an epidemiological emergency (something that was previously stated), one of the most important challenges is how to manage this information once it reaches the government authorities. The decision on how and when information will be released to the general public ends up at the top level of a government, usually the President or Prime Minister. The decision will be driven by many factors, overall, the economic impact that could have the release of such information to the public. However, governments need to rethink and define immediately laws and policies based on firm moral grounds that clearly state that, under an epidemiological emergency, key data will be collected and shared through a central organization and that will finally create the possibility to report at least the above-mentioned indicators.
As of today, there are guidelines, mostly weak, in regard on how to proceed with providing the information to the entities that coordinate the global efforts of a pandemic, but this has not been reinforced. Undoubtedly, there is need that countries agree to develop such laws and policies within their countries, and after passing these laws locally, this must be communicated to a centralized organization body and abide by such laws and policies to move forward and begin to have a universal system that collects such data and communicates such data around the globe.
An important aspect of all this is that transparency is deeply rooted in moral arguments more than legal. The implications to abide such laws and policies will be of key importance in order to develop trust in the general public, and again, trust is of key importance when managing an epidemic crisis. The teams who will need to discuss the laws and policies must write them based on firm arguments that will stand even in the most difficult and perilous situations. COVID-19 has shown us how the lack of transparency can undermine any effort directed to mitigate the effect of pandemic. Even more important, transparency could create an environment of peace instead of conflict between nations, which has been an important subject with deep effects, like the one raised by the United States and Chinese governments 26, 27 or more locally like the one in Guatemala where the lack of transparency by the government ended up in the distrust of the population and therefore the increased number of cases and unmanageable situation of the pandemics.

Conclusion
In conclusion, data collection and transparency are two important topics closely related with strong impact in the appropriate management of an epidemiological emergency. COVID-19 has thought us globally and locally that economic impact drives the decision on how the data is obtained and what is released to the public. So far, both in high-income countries like China or low-middle-income countries like Guatemala, there is a perception that the data was flaw and inaccurate 28 , and therefore, that lead to a situation of distrust that worsened the crisis. It is proposed that based on the lessons learned, that a centralized organization, whether this be WHO or WTO, collects few but substantial data that could be used for global and local decisions, data like number of positive tests, positive swabs and autopsies per day should be considered, but is not limited to this three, as there are other important demographic and clinical data that could be obtained and reported. In addition, local laws and policies related to transparency should be discussed and approved by governments in order to develop trust in the public opinion, which plays a key role in the ethical, legal, and appropriate way to manage an epidemiological emergency like the one we have experienced with COVID-19.


Assessing the Impact of COVID-19 Pandemic on the Regions’ Socio-Economic Development: The Case of Ukraine

Solving the problems of regional development belongs to the category of strategic and most important of each country. The COVID-19 pandemic has become the biggest challenge for the world economic system, causing a significant impact on the reduction of key macroeconomic indicators, changes in business conditions, which has raised the issue of assessing the social and economic development of regions. The paper considers the application of composite index assessment technology for the consequences of COVID-19 on the development indicators of Ukraine's regions. The comparison was conducted according to the data of the first two quarters of 2019 and 2020. For the study, eight indicators were selected, which by content feature were divided into a subset of economic indicators and a subset of social indicators. A partial composite development index was designed for each subset. The principal components method was used to calculate the weights of the components. The results of the analysis showed that the COVID-19 pandemic had a greater impact on economic development: for each region, there is a decrease in the value of the indicator. While for a partial composite index of social development such a decrease is less noticeable. The reflection of the regions in the space of these composite indices showed that their structure remained virtually unchanged. The analysis of the common composite index of regional development, designed by the convolution of partial composite indices indicators, also showed a decrease in its values in 2020. The paper analyses the measures taken by the Government of Ukraine to neutralize the effects of the pandemic.

Problem Description
The pandemic COVID-19 caused by SARS-CoV-2 proved to be the most unpleasant peacetime shock for the world economy in the current century. There is every reason to consider that from an economic point of view, this crisis will be deeper than in [2008][2009]. At that time, the crisis was triggered by a demand shock from the spread of toxic financial assets around the world, while the current crisis is an unprecedented situation that is the result of a pandemic alone. The views of scientists, politicians, physicians on its duration, depth, consequences, and financial costs of their elimination are currently not unanimous. At the same time, human losses and economic damage are already evident, both for countries with developed economies and for those in developing countries. Thus, according to calculations by the International Labor Organization (ILO), estimates of income losses indicate a global decline of 10.7 per cent during the first three quarters of 2020 (compared to the corresponding period in 2019), which amounts to USD 3.5 trillion, or 5.5 per cent of GDP for the first three quarters of 2019. Loss of income from work in countries with below-average incomes reached 15.1 per cent in lowermiddle-income countries and 11.4 per cent in upper-middle-income countries. The estimated total loss of working time in the second quarter of 2020 (relative to the fourth quarter of 2019) is now 17.3 per cent or 495 million full-time equivalent jobs. Countries most affected by below-average incomes, which are estimated to have reduced working hours by 23.3 per cent (near 240 million FTE jobs in the second quarter of the year) (ILO, 2020). According to the World Bank (2020), the baseline forecast assumes a reduction in world GDP by 5.2 per cent in 2020 -the deepest global recession in decades, despite the extraordinary efforts of governments to counter it through fiscal and monetary policy. In the long run, the deep recessions caused by the pandemic will leave long-term scars due to declining investment, erosion of human capital due to job losses and training, and fragmentation of global trade and supply. According to forecasts, the developed economy will shrink by 7 per cent. This negative impact will also affect the prospects of developing countries, where the economic downturn will be 2.5 per cent. The COVID-19 pandemic and severe restrictive measures aimed at preventing its spread have significantly affected the real business environment in Ukraine. As a result of the introduction of quarantine, the financial condition of large and medium-sized enterprises deteriorated, and a significant share of small enterprises ceased to operate. The main trends and problems of socio-economic development of regions in the context of national challenges caused by a pandemic presented in the State Strategy for Regional Development for 2021-2027(CMU, 2020a, which was developed by the Cabinet of Ministers of Ukraine. It reflects forecasted key macroeconomic indicators for the end of 2020: falling GDP -4.8 percent, inflation -11.6 percent; unemployment rate -9.4 percent; fall in average wages -4.5 percent to 10.7 thousand hryvnias; fall in exports -5.5 percent, fall in imports -10 percent. An even more pessimistic forecast for Ukraine's economic development is based on a study conducted by the German Economic Team (GET, Berlin) in collaboration with the Institute for Economic Research and Policy Consulting (IERPC, Kyiv). GDP will shrink by 7% in 2020 as a result of the impact of external and internal shocks on the economy. Under the previous forecast, before the pandemic, GDP was expected to grow by 3%. According to the pessimistic scenario, which envisages longer quarantine measures in Ukraine and stronger external shocks, the economic downturn will be 11.2 per cent (Ukrinform, 2020). However, according to the authors of the study, since Ukraine's economy was in good shape when the pandemic began, its impact will not be as strong as the impact of the crisis of 2009, which led to a reduction in GDP by 15 per cent. The government also has room in its policy to support the economy. Also important for overcoming the economic crisis are Ukraine's recent laws on the banking sector and the land market, as well as new IMF programs that will stabilize government spending. To minimize the negative socio-economic consequences of the COVID-19 pandemic, it is necessary to assess existing trends, anticipate different scenarios for further development of the situation, carry out calculations to obtain data that will be the basis for rational science-based managerial decisions. These facts highlight the need for research to assess the real losses from the COVID-19 Pandemic in terms of regional socio-economic development, which will help identify weaknesses in national regional policy and contribute to the achievement of the goals reflected in the State Strategy for Regional Development for 2021-2027.

Literature Review
Despite the relatively short period of the COVID-19 pandemic spread, a significant amount of research has already been conducted to assess and overcoming its effects. It should be noted that at the same time there is a lot of studies on the impact of previous pandemics on economic development, in particular, their influence on macroeconomic indicators of development. In particular, Cavallo, Galiani, Noy & Pantano (2013), Bloom & Canning (2004) emphasize the need to anticipate and manage future risks of pandemic spread. In paper (Jonung & Roeger, 2006), based on the use of a quarterly macroeconomic model, estimates of GDP growth due to the pandemic in the EU in 2006 are given. The indirect economic impact of a pandemic based on general equilibrium models is presented in paper (Burns, Mensbrugghe & Timmer, 2006). The study (Thomas et al., 2015) reflects the results of the evaluation of the impact of the Ebola epidemic on GDP reduction in West Africa's low-income countries. Although research on the impact of pandemics on economic development reflects declining macroeconomic indicators, the authors of these studies agreed that this is not likely to be a serious threat to global macroeconomics. Scholars' assessments of the consequences of the COVID-19 pandemic are less optimistic. Although most of them agree that it is difficult to accurately estimate the duration, further spread, and consequences of the impact of negative processes on the development of regions today, the most optimistic forecasts predict a way out of the crisis only in a few years. Economic and mathematical modeling is an important tool for assessing current trends in the development of situations of such situations and predicting possible consequences. Grace Gondwe's study (2020) presents a macroeconomic model that assesses the possible effects of COVID-19 on African economies and provides forecasted indicators' values based on global scenarios. These estimates should not be taken as definitive predictions due to the focus on global shocks affecting trade between Africa and the rest of the world. All other direct effects of COVID-19 on productivity and government spending in Africa remain unchanged. Moreover, the presented analysis does not take into account domestic and multilateral measures used to mitigate the impact of COVID-19 on the African countries under study. The paper (Gallagher, 2020) on the example of Indonesia examines the direct impact of COVID-19 during the crisis on the indicators of total production, employment, and poverty. It also includes information on Indonesia's macroeconomic resilience and its ability to respond to the crisis using indicators like rapid inflation, volatile fiscal deficits, or rapid currency depreciation. The study presents three scenarios for GDP changes, taking into account the forecast published by the IMF: pessimistic, moderate, and optimistic ones. The author highlighted that results will help develop measures to improve the situation and prepare for post-crisis recovery. Al-Baidhani (2020) compared countries by level of social and economic development. To this end, the author used the Human Development Index (HDI), developed by the United Nations. The sample included countries both with developed and developing economies. The author also presents the sectors of the economy most affected by the pandemic in these countries, as well as estimates of GDP change. In the paper (Estrada, 2020), to assess the consequences of the pandemic, a new indicator "The Economic Uncontrolled Desgrowth from COVID-19" (-δ CO-VID-19), is proposed. It reflects the negative impact of the pandemic on GDP formation. The author presents the use of this indicator in the study of scenarios of world economic development and changes in global GDP and analyzes possible measures aimed at implementing these scenarios. To highlight the consensus vision of future trends and objective assessment of risks and challenges facing the world economy, the Ministry for Development of Economy, Trade, and Agriculture of Ukraine, in cooperation with the UNICEF in Ukraine, prepared the Consensus Forecast entitled "Ukraine in 2020-2021: Aftermath of the Pandemic" (Nikolaichuk et.al., 2020) in which three scenarios of development of the domestic economy are given and the most probable forecast scenario for 2020-2021 is substantiated. It reflects the average values of the main forecast indicators of economic development of Ukraine, which are calculated as the median based on expert assessments of survey participants of leading experts in the field of macroeconomic analysis and forecasting. It should be noted that for values of GDP and unemployment, the differences between the studied development scenarios are not significant. At the same time, the estimates of the consumer price index differ quite significantly -according to the forecast based on a single scenario, they are higher, and the parameters of the exchange rate towards higher devaluation also differ, especially in 2021. At the same time, the average forecast is significantly closer in its parameters to the Government forecast, except for the USD exchange rate. We note, that the IMF forecast for the dynamics of GDP in Ukraine, which reflects the reduction of this indicator by the end of 2020. by 8.2 per cent, is the most pessimistic among all comparable forecasts. Inflation parameters are as close as possible to the parameters of the consensus forecast. To assess and identify structural imbalances in regional development, the use of a composite index is quite common. This approach is reflected, in particular, in publications (Rondinella & Segre, 2014) (Hryhoruk, Khrushch & Grygoruk, 2020) (Royuela, 2020). However, its application to assess the effects of a pandemic in recent studies has received insufficient attention. The results of the analysis show that most studies reflect rapid assessments of the socio-economic impacts of COVID-19 with an emphasis on trends and potential scenarios and are mainly focused on assessing GDP change as one of the most important macroeconomic indicators. At the same time, research at the level of assessing changes in development trends in individual regions of the country is practically not presented. Our study aims to develop an approach to the analysis of the impact of COVID-19 on the level and structure of socio-economic development of the regions of Ukraine, through the use of composite index assessment technology, principal components method, and graphical data visualization. We use composite indices to comprehensively assess the impact of the pandemic on the regions' socio-economic development and the change in the structuring of regions concerning these indicators. We use the principal components method to determine the weight of each initial indicator when designing composite indices.

Research Methodology
The composite (comprehensive) index assessment technology is aimed at reducing the indicator space of the studied phenomenon to describe it more compactly. The studied characteristic, which often has the form of latent quality, which is not subject to direct measurement and description, is usually described by some set of measured indicators. A fairly common approach is when the assessment is based on a complete reduction of the initial set of indicators. That is, the final result of calculations is a single composite (comprehensive) index, which accumulates all the information contained in the original set of indicators. This simplifies the further interpretation of the results. When designing a composite index, the following requirements must be taken into account: • change of its positive quality should correspond to the directions of "advantage" of its components; • the composite index should take into account the informativeness of all its components and at the same time allow the compression of redundant information contained in them; • it should reproduce as much as possible the variation of partial indicators based on which it is designed; • the importance of each partial indicator must be taken into account; • weights for its components must be statistically significant. For correct use and clear interpretation of the results it is necessary, that the composite index had the following properties: • spatial comparability, i.e. the possibility of comparing the index values for different objects under study; • differentiating ability, i.e. it must be sufficiently informative and provide an opportunity to distinguish between individual objects of the initial data set; • the simplicity of interpretation, i.e. the result must have a clear, understandable and clear interpretation; To ensure the above requirements for the composite index designing procedure, the initial indicators X={X1, X2,…, Xn} should be presented in the form of stimulants. This will provide a positive correlation with the characteristic under study. The removal of the influence of units of measurement is achieved by normalizing the values of the initial indicators, usually by reducing their values from 0 to 1. These requirements are provided by using the transformation (Hryhoruk, Khrushch & Grygoruk, 2019b): .m, j=1..n; m -is the number of objects under study (in this case -regions); n -is the number of initial indicators. In cases where the indicators Xj are relative indicators of the dynamics, the transformation should be carried out according to the formula: (2) The procedure of data normalization can be carried out according to other rules, depending on the origin of the indicator. A weighted additive or multiplicative convolution is used as the synthesizing function Q to determine the value of the composite index: If the initial values of Xj are values measured on an absolute scale, then, in our opinion, it is advisable to use additive convolution. If the initial indicators are relative indicators of dynamics, then it is advisable to use a multiplicative convolution. Therefore, in the case when among the selected indicators are both absolute and relative measured, it is proposed to use block convolution by the formula: where Qi -is a result value of composite index; QAi -is a value of the partial composite index, that is calculated by the formula (3) using the indicators measured by absolute scale; QMi -is a value of the partial composite index, that is calculated by the formula (4) using the indicators measured by the relative dynamic scale; wA, wM -are weighted coefficients of partial composite indices; i=1..n. When choosing the set of initial indicators, it should be borne in mind that the presence of a large number of them complicates the composite index designing procedure, negatively affects the significance of weight coefficients, and, consequently, reduces its informativeness and discriminatory ability. In this case, it is advisable to divide the set of initial indicators into groups, each of which reflects a certain property of the studied characteristic. For each group, it is necessary to calculate its partial composite index using one of the formulas (3), (4), and formulas (6) for the final result if is needed. The common composite index is calculated by the formula: where QCOM i -are the values of common composite index; Qsi -are values of partial composite indexes for groups of initial indicators; vs -are weight coefficient values for partial composite indexes; they should meet the condition like the formula (5); k -is a number of groups. Determining the weight coefficients for both the set of initial indicators and for partial composite indices in the case of group convolution is a non-trivial task. Quite common is the approach in which all components of the composite index are equal. This approach simplifies the calculations but enhances the effects of compensation when the high values of some indicators are offset by the low values of others. Another approach is to use the results of an expert survey to establish weights. We use an approach based on the application of methods of multidimensional statistical analysis, in particular, the principal components method. The weights are determined in proportion to the absolute values of the factor loadings of the first principal component: where nj -is a number of initial indicators in a j-th group, j=1..k. In our study, we use the described above approaches to identify the weight coefficients.

Results and Discussion
Let us assess changes in the socio-economic development of Ukraine's regions due to the impact of the COVID-19 pandemic. As initial indicators, we chose two groups of indicators. The first reflects the economic component of regional development, the second -social one. The information source for the calculations was the data of the State Statistics Service of Ukraine (SSSU, 2019) (SSSU, 2020) and the Ministry for Communities and Territories Development of Ukraine (MCTDU, 2020). To achieve the possibility of comparing the results, we chose the first two quarters of 2019 (pre-quarantine period) and the first two quarters of 2020 (the period of the COVID-19 pandemic) as the periods for Published by ECSDEV, Via dei Fiori, 34, 00172, Rome, Italy http://ecsdev.org the calculations. As initial indicators, we chose such. For a group of indicators of economic development: XE1 -Volume of sold industrial products per capita, UAH; XE2 -Volume of agricultural production per capita of the rural population, UAH; XE3 -Volume of construction works performed per capita, UAH; XE4 -Volume of capital investments per capita cumulatively since the beginning of the year, UAH; XE5 -Exports of goods per capita, USD. For a group of indicators of social development: XS1 -Unemployment rate of the population; XS2 -Employment rate of the population; XS3 -The volume of housing commissioned per 10 thousand people, sq. meters of total area. It should be noted that the GRP per capita indicator is quite representative and important for the analysis of the socio-economic development of the regions, but at the time of preparation of this article statistics for this indicator for the first two quarters of 2020 aren't available.
For compact use of Ukraine regions' names, we assigned to each of them the corresponding code which we used further for the designation of each region (Table 1). The values of initial indicators for calculations are shown in tables 2 and 3. To simplify the display of data in the tables, the corresponding period is denoted only by a year, bearing in mind that real data reflect the values of indicators only for the first two quarters of the appropriate year.   Next step, we normalized the data. For a more objective comparison of the results of calculations when performing this procedure, the data for 2019 and 2020 for each indicator we combined into one sample. This allowed adequate tracking changes in the value of the calculated composite index. Considering, that all data are indicators, measured on an absolute scale, the normalization procedure has performed by formula (1). Note that XS1 is a disincentive. and the other indicators in both groups-stimulants.
To obtain the weight coefficients of the initial indicators for each group, we calculated the correlation matrices. The results of the calculations are shown in Tables 4 and 5. Note that in this case, we also combined the values of the indicators for two time periods in one sample, and thus obtained one correlation matrix for each group of indicators  The calculated values of the factor loadings of the first principal component for the corresponding group of indicators and obtained by them the values of the weight coefficients calculated by the formula (8) are given in Tables 6, 7.  Next step, we calculated the values of the partial composite indices Q1 and Q2 and the common composite index QCOM. To reach this aim, we used the formula of linear weighted additive convolution (6) to calculate partial composite indices, and formula (7) to calculate the values of the common composite index. The corresponding weight coefficients were calculated by the formula (9). The results of the calculations are listed in Table 8. Let's compare the values of partial composite indices for the first two quarters of 2019 and the corresponding period of 2020. To do this, we considered the graphical interpretation of the results (Figures 1, 2). According to the analysis of the presented figures, there are changes in the socio-economic development of regions during the study period. The values of the indices for 2020 are less than the corresponding values for 2019. Therefore, we can state that the COVID-19 pandemic harmed the socio-economic development of each region of Ukraine. According to the results of January-June 2020, as a whole, there were negative trends in the dynamics of production in key areas of development: industry, agriculture, construction, and capital investment, for most Ukraine's regions. This fact was evidenced by the main socio-economic indicators presented in Table 2. The decrease in our calculated partial composite index of economic development is especially noticeable for Vinnytsya (r_1), Dnipropetrovsk (r_3), Zaporizhya (r_7), Mykolayiv (r_13), and Kherson (r_20) regions, which is explained by a significant decrease in the values of baseline indicators that Published by ECSDEV, Via dei Fiori, 34, 00172, Rome, Italy http://ecsdev.org were used for calculation appropriate patrial index. In particular, a significant decrease in industrial production was observed in Dnipropetrovsk (-17.6 per cent) and Zaporizhya (-11.4 per cent) oblasts, which are historically industrial centers of Ukraine. In January-June 2020, the volume of gross agricultural production per capita decreased the most in Odesa (by 66.8 per cent), Zaporizhya (by 52.0 per cent), Mykolayiv (by 51.4 per cent), Dnipropetrovsk (by 27.6 per cent), Kherson (by 22.2 per cent) regions. For the partial composite index of social development, the largest decrease for its values was for Ivano-Frankivsk (r_8) and Chernivtsi regions (r_23). This is since these regions were the first, where strict quarantine restrictions were introduced, which harmed the indicators of social development selected for analysis. At the same time, for most regions, the value of this index has either not changed or is insignificant, and for Luhansk (r_11), Kharkiv (r_19), and Khmelnytskyi (r_21) regions there is a slight increase in the values of this index.   The greatest reduction of the common composite index value takes place for the Donetsk region (r_4) -by 26 per cent, Zaporizhya region (r_7) -by 24 per cent, Mykolaiv region (r_13) -by 23 per cent, Ivano-Frankivsk (r_8) and Kherson (r_20) regions -by 20 per cent. On average, the reduction of the common composite indicator is 12 per cent. It should be noted that for the Khmelnytskyi region (r_21) the value of the indicator remained at the same level, for the Rivne region (r_16) the decrease was 3 per cent, Cherkasy region (r_22) -5 per cent, for Sumy region (r_17) -6 per cent. Note that in these regions in the first half of 2020 there was the lowest in Ukraine incidence of COVID-19. The analysis of the structure of regions in the space of partial composite indices (Figures 4,5) shows that in general there were no changes, the grouping of regions in the space of selected indicators remained unchanged. Four units can be distinguished: Dnipropetrovsk (r_3) and Kyiv (r_9) regions, which have rather high values of indicators, and Donetsk and Luhansk regions (r_4 and r_11 respectively), where the level of these indices, especially the social development, is quite low. For the rest of the regions, there is a fairly dense grouping, although it should be noted that somewhat separately in this group can be distinguished Poltava (r_15) and Published by ECSDEV, Via dei Fiori, 34, 00172, Rome, Italy http://ecsdev.org Kharkiv (r_19) regions. Among the factors that continue to harm the socio-economic development of both the country as a whole and individual region, we note the following.
Falling GDP of trading partners causes a reduction in exports of goods. Indirectly, we should also expect a decrease in commodity prices, the share of which at the end of 2019 in domestic exports was 80 per cent. Restrictions on international passenger services, the closure of many European labour markets, and declining demand for exports of services, particularly in the IT sector, negatively affect remittances from abroad, which averaged about 8 per cent of GDP annually during 2015-2019, and is an important source of income for Ukrainian households, especially for the western regions of Ukraine. Also due to border closures and quarantine measures abroad, a large number of Ukrainian labor migrants remained in Ukraine who returned to the country at the beginning of the COVID-19 pandemic and did not find decent employment here, which negatively affects the unemployment rate. Declining demand for goods and services in domestic markets also causes lower production. The decline in agricultural production will be expected, primarily crop production, which, in addition to the negative economic consequences associated with Covid-19, is caused by deteriorating yields due to unusually dry weather in July-August this year.
In times of crisis, international investors usually leave emerging markets, creating a balance of payments crisis and pressure on the local currency. The inflow of foreign direct investment in Ukraine almost stopped at the beginning of the pandemic, and the net outflow of portfolio investment amounted to USD 0.85 billion (Dienkov, 2020). It should also be noted the reduction of international reserves to USD 25.4 billion, or 4.4 months of future imports as of the end of June 2020 (NBU, 2020a). Ukraine should negotiate further cooperation with the IMF to stabilize its foreign exchange market and create comfortable foreign exchange reserves to be prepared for any emergencies that are caused by the crisis that may occur in the future. Without a support program, the probability of default increases significantly, resulting in inevitable problems and losses.
To neutralize the impact of these negative factors, the government has implemented a number of measures aimed at supporting financial markets, businesses, and individuals. In particular, they are reflected in the adopted regulations, like the State Strategy for Regional Development for 2021-2027 (CMU, 2020), adopted on August 5, 2020, and the State Program of stimulation of the economy to overcome the negative effects caused by restrictive measures to prevent the occurrence and spread of acute respiratory disease COVID-19 caused by coronavirus SARS-CoV-2, for 2020 -2022 (CMU, 2020b), adopted on May 25, 2020. These documents provide for the implementation of a comprehensive system of new opportunities for stabilization and sustainable development of Ukraine's economy, in particular, through economic incentives for digitalization, development of import substitution of goods and services while maintaining export potential, increasing employment by maintaining existing and stimulating new high-productivity jobs. with decent working conditions. Both monetary and fiscal instruments of influence on economic development are also used. In particular, the National Bank of Ukraine lowered the Key Policy Rate, which is 6 per cent from September 2020 (NBU, 2020b), which should also act as an additional stimulus to economic development, in particular, reduce the cost of lending. The government should also consider financial incentives to support both people and businesses experiencing temporary financial difficulties. The source of such incentives are loans from international financial organizations, even by increasing Ukraine's national debt.

Conclusions
Today, Ukraine, like the rest of the world, faces a new challenge -the pandemic of the acute respiratory disease COVID-19, caused by the coronavirus SARS-CoV-2, which forced the introduction of restrictive measures to prevent the spread of COVID-19. This negatively affected the activities of the business in all sectors of the economy, foreign economic activity, caused changes in the internal and external environment. The global economy is approaching one of the worst recessions in its history. New trade barriers appear, international investment decreases, the labour movement is limited Forecasts made by both domestic and foreign institutions predict a significant decline in all macroeconomic indicators by the end of 2020. In Ukraine, which has always been more vulnerable to crisis phenomena, the fall in the gross domestic product is projected at 4.8 percent. We propose an approach to the analysis of the impact of COVID-19 on the level and structure of the socio-economic development of the regions of Ukraine, which is based on the use of composite index assessment technology. A set of initial indicators was selected for the study, which was divided according to the content characteristics into a group of indicators of economic development and a group of indicators of social development. The research was conducted according to the data of the first half of 2020 and the same period of 2019. The comparability of the results was also ensured by combining the original data for each indicator for two periods of time into one sample. The corresponding partial composite index was designed for each group. The analysis of the results showed a decrease in the values of the partial composite index of economic development in 2020, which we attribute to the change in business conditions under the influence of the pandemic. For a partial composite index of social development, such changes are not so obvious that can be explained by certain inertia of indicators of employment and unemployment. At the same time, the structural characteristics of the location of regions in the space of partial composite indices remained almost identical. The calculation of the common composite index of socio-economic development also showed negative changes in 2020, which largely depend on the reduction of the values of the partial composite index of economic development, the weight of which in the final result is higher. We considered the measures taken by the Government of Ukraine to neutralize the effects of the pandemic and stabilize the situation, in particular, the government's regional development programs, the measures of the National Bank of Ukraine. The results of the study can be taken into account by public administration as analytical analysis of the situation to shape the regional development strategies. Prospects for further research in this area are to expand the information base for calculations, taking into account indicators of nonmetric nature, in particular, rating data, as well as the inclusion of environmental components. It will allow studying the development of Ukraine's regions from the standpoint of their sustainable development.


Can electric vehicles be good for Sub-Saharan Africa? Energy Strategy Reviews

siloed transport and electricity sectors could evolve to support each other in the future.

Introduction: why high-income country approaches to electrifying transport will not work in Sub-Saharan Africa
Electric Vehicles (EVs) in High-Income Countries (HICs) have several common characteristics: they are considered high-end, mass-manufactured, private passenger cars operating in urban areas, supported by national subsidies, and introduced with the confidence that the electricity sector will ensure there is sufficient generation to meet the demand they induce. By comparing these characteristics with the Sub-Saharan Africa (SSA) context, we identify three core reasons why HIC approaches to vehicle electrification should not be shoehorned into SSA: (i) the mobility patterns and vehicle characteristics of the transport systems, (ii) the availability of capital, and (iii) the unreliable state of the electricity systems.
Firstly, the characteristics of SSA transport systems are fundamentally different to those in HICs [5]. In SSA, the majority of journeys are undertaken using privately-owned and informally run "public" transport vehicles, known as paratransit [6], which are demand-responsive, and often under-considered by transport planners [7]. Paratransit vehicles include motorbike taxis (e.g., boda-bodas), 16-seater minibuses (e.g., matatus), and auto-rickshaws (e.g., tuk-tuks) [8,9]. Paratransit vehicles meet the demand for 50-98% of automotive passenger trips in SSA cities [10]. In contrast, in the UK, 13% of automotive journeys are conducted using public transport while the vast majority (85%) are completed in private cars [11]. Given these differences between the transport systems, the private EV model is not suitable for the majority of transport needs in SSA. Instead, innovative approaches to SSA-specific EVs (e.g., minibuses and motorbikes) will need to be developed, along with appropriate business models, targeted at the paratransit vehicle owner-operators. Due to its dominance in SSA, this Viewpoint focuses on paratransit.
Secondly, the availability of capital is significantly lower in SSA than in HICs. Due to a lack of capital, the majority of vehicles are bought preowned from HICs. In Africa, 60% of annual registrations are of preowned vehicles [3]. In some countries, like Nigeria and Uganda, it can be as high as 90% [12,13]. These second-hand vehicles are reported to have poor safety and environmental standards [3]. In light of these considerations, to foster the transition to EVs, the price must be acceptable to the owner-operators, close to that of pre-owned Internal Combustion Engine (ICE) vehicles.
Thirdly, the power system is unreliable and insufficient in many countries in SSA [14]. For example, in Sierra Leone there were 53 unplanned blackouts per day throughout 2017. 1 Even in South Africa, one of the more affluent countries in SSA, rolling blackouts are not uncommon [15]. In HICs, the expectation is that power will be available when required; evidently the same cannot be said for countries in SSA. Therefore, it is even more important that the electrification of transport is developed hand-in-hand with the electricity system. None of the above rule out EVs in SSA, but they do explain the historically low uptake of EVs in this region [4] and highlight the need for innovative approaches, developed with the context in mind. In fact, we propose that if introduced appropriately, EVs could offer benefits to SSA beyond the potential for emissions reductions. These benefits could provide a powerful motivation for pathway development.

How might EVs be good for SSA?
Assuming that passengers are technology-agnostic provided they get from A to B without inconvenience, we consider the benefits EVs in SSA could offer to three main stakeholder groups: (i) governments, (ii) electricity providers, and (iii) owner-operators.

Governments
The first benefit to governments is the potential for emission reductions. Emission savings can be calculated by considering the national electricity generation mix and the increased efficiency of an EV compared to an ICE (roughly 90% efficient compared to 12-40%) [16]. In Fig. 1(a) we calculate the potential emissions saving from switching from an ICE vehicle to an EV for each country in SSA. As shown in Fig. 1 (a), and in work by Knobloch et al. [17], in all SSA countries electrification of transport would reduce emissions immediately considering the current electricity mix. The highest emissions reductions are possible in countries such as Ethiopia, Uganda, the Democratic Republic of the Congo (DRC), and Namibia. However, even in countries where the emissions reductions are not so pronounced (e.g., South Africa, Botswana, and Niger), electrification of transport still offers the advantage that as electricity generation is decarbonised in the future so, simultaneously, is transport [18]. The second benefit EVs can offer is improved air quality, especially in urban areas. In SSA, transport attributable particulate matter and ozone were responsible for nearly 4500 deaths in 2015 [19]. Improved air quality results in a positive effect on population health [1], along with the associated economic benefits from, for example, reduced health care spending and fewer lost working days [20]. Another benefit of EV adoption is directly economic. Many governments in SSA provide drastic fossil fuel subsidies, which can be a drain on financial resources. For example, in Botswana and South Africa the 2017 petroleum subsidies were US$135 and US$194 per capita, respectively [21]. Fig. 1(b) shows the post-tax government spending on fossil fuel petroleum subsidies per person according to the International Monetary Fund. Subsidies distort the market and can result in increased consumption of fossil fuels. By converting to EVs, money could be diverted from fossil fuel subsidies to financing cheap, clean electricity generation and fossil fuel consumption could be reduced. Often these subsidies are adopted to avoid fuel poverty, which must be considered in any subsidy reform. In countries that also employ fuel taxes alongside subsidies, for example Ethiopia [22], reduced fossil fuel consumption will result in reduced tax income, which may need to be recovered by other means. However, some advantages to reduced fossil fuel consumption still exist in these contexts. A reduction in fossil fuel imports can both increase geopolitical independence and reduce the strain on a government's often limited foreign currency [23]. Of course, for the small number of countries in SSA that produce oilsuch as Nigeria and Angola [24] the benefits may be more questionable, but this will be the case for any motion to depart from a fossil-dependent economy.

Electricity providers
The main benefit of EV uptake for electricity providers is increased revenue. In SSA the electricity providers are often Independent Power Producers or state-owned utilities, many of which are struggling [25]. EVs will create increased energy demand and essentially act as an anchor load which boosts revenue to providers. If half of the road transport were electrified, this would create a demand of 200 TWh per annum across SSA, a market which could equate to US$14 billion under current pricing (calculation in appendicies). To meet this demand, additional clean energy capacity will likely be necessary (e.g., from solar photovoltaics (PV)) [26]. The profits earned could be re-invested to increase clean generation capacity or improve electricity systems overall. Additionally, EVs could offer an opportunity to improve grid reliability through Vehicle-to-Grid (V2G) or Vehicle-to-Home (V2H). By using the battery within the EV as an energy storage asset, which can inject electricity back into the grid, house or building in times of need, thus improving electricity reliability [27]. This is especially relevant as the capacity of renewable energy generation increases.

Owner-operators
We consider there to be two main benefits of EV adoption for paratransit owner-operators resulting from the development of SSA specific EVs: (i) cheaper operating costs, and (ii) lower vehicle capital costs compared to EVs designed for HICs. Firstly, lower operating costs compared to ICE vehicles are possible due to more efficient vehicle drivetrains and the difference between the price of electricity and vehicle fuel. The cost savings are shown in Fig. 1 (c) for various SSA countries. In all SSA countries (except Liberia), it is cheaper per kilometre to operate an EV instead of an ICE, resulting in reduced total cost of ownership. In some cases, such as the DRC and Zambia, cost savings are over US$0.15/km. Annually, in these countries, this can translate to a cost saving of US$3900 per vehicle, see appendicies for details. If fuel subsidies were removed, the saving per kilometre for an EV compared to an ICE would increase even further.
Secondly, currently, for many owner-operators a new vehicle is unaffordable [28]. The vehicle capital cost is considered a key barrier to uptake. Therefore, to lower vehicle capital cost, affordable vehicles must be designed and manufactured. This could be achieved through local manufacturing of SSA specific EVs, such as the e-motorbikes manufactured by Ampersand in Rwanda and the e-buses being built in Uganda [29]. Alternatively, retrofitting vehicles to be electric could lower prices even further and could be a more widely achievable option. Innovative financing or leasing could also help to lower the burden of capital cost of vehicle ownership.
Although these benefits may provide significant motivation for EV adoption, challenges remain, not least surrounding how these vehicles would charge.

The elephant in the room: EV charging
As discussed, electricity systems in SSA are notoriously unreliable. Additionally, distribution networks are often constrained in their technical capacity. At first glance, the prospect of adding an additional load in the form of EV charging may appear at best daunting or at worst foolish. This is further complicated because not all locations suitable for EV charging currently have access to the electricity grid.
However, the electricity generation mix is transitioning to incorporate greater renewable capacity. With the falling cost of renewable energy, and climate change commitments as part of the Paris Agreement, SSA countries are shifting from centralised fossil-fuelled power plants towards clean renewable generation, exploiting their abundant natural resources. For example, Kenya now has over 820 MW of geothermal capacity [30] and is home to the largest wind farm in Africa which is over 300 MW [31]. In 2018, US$2.8 billion were invested into renewables in SSA (excluding South Africa). As part of this an additional 440 MW of PV capacity was installed [31]. In other countries, such as South Africa, Ethiopia, and Tanzania, PV generation shows significant potential in the range of 8-37 GW [32]. Co-locating PV with EV charging not only provides additional generation to meet this new demand, but also eases constraints on local distribution networks and mitigates the need to reinforce the network.
For those installing generation, the aim is always to maximise the units of electricity sold. Novel, context-specific EV solutions may provide an answer to this. For instance, EV charging could be coordinated with times of surplus generation to "soak-up" any excess energy. This "smart charging" has been shown to reduce requirements for additional generation capacity and network reinforcements [33]. In comparison, uncontrolled charging, which is when vehicles charge at full power as soon as they plug in, could double peak power demand as was found in a Kenyan case study [34].
However, one cannot assume that vehicles are available for charging at all times. Local mobility patterns must be taken into consideration when determining the most appropriate technical option. For example, unlike private cars in HICs, which are parked 95% of the time, paratransit vehicles in SSA have a higher usage to provide mobility services. Technical solutions that are appropriate to the application must be selected.

Technology choices to enable EV integration
To identify the most appropriate EV charging options, we present a deep dive into two of the aforementioned paratransit vehiclesthe minibus taxi and the motorbike taxiand three EV charging technologies: battery swap, plug-in charging, and on-board PV, each described below. We will consider the suitability of said technologies under different usage scenarios, when electricity for charging is provided by co-located PV. In other words, the batteries must charge during daylight hours.
Battery swap requires vehicles to be designed so that the battery can be removed and replaced with a fully charged battery within minutes [35]. This allows the battery to be charged whenever there is excess power generation and at times when the vehicle is not stationary, minimising generation curtailment. For example, battery swap could allow vehicles that are used during the day to swap their batteries that evening for a twin battery which has been outside the vehicle, using solar PV to charge during the day. The pattern then repeats the next day. In this way, battery swap decouples charging from driving patterns, which can be advantageous to vehicles that do not spend much time parked. The challenges are that a vehicle must be specifically designed to allow this, multiple batteries are needed per vehicle, and a suitable battery swap station network is required. All of these can be expensive and the battery swap business model has been seen to fail for cars in some HICs in the past (e.g., Better Place in 2013 [36]). However, in Taiwan, this model has been especially successful for motorbikes in recent years, with the company Gogoro now expanding its business model to India [37].
Plug-in charging, in this work, refers to vehicles which are plugged in and charge from stationary solar PV. Therefore, the vehicles must be parked at a charging point for sufficient time during the day in order to charge. It is assumed that the solar PV is installed at a capacity able to meet the EV demand during hours of generation. Solar PV covered EV parking bays offer a clean charging solution at the same time as providing shade [26]. The challenge is that the vehicle must be out-of-use and plugged in for sufficient daylight hours to charge. This needs to be carefully considered in conjunction with vehicle operating hours to make sure charging does not interfere with mobility service offerings. For many minibuses this may work well as they operate predominantly during commuter-hours and can be stationary during the middle of the day.
On-board solar is when solar PV is placed on the body of the vehicle. This is best suited to minibuses which have a larger body area, and this, therefore, is not considered for motorbikes in this work. The presence of PV on the vehicle body allows the vehicle to charge wherever it is during the day, whether it is parked or in motion. This reduces the energy demand of the vehicle when it is plugged in and reduces the number of daylight hours during which the vehicle must be parked and charging [38]. This technology is not currently widely available, but there is active research and development in the area with the Fraunhofer Institute recently commencing project 'Lade-PV' which integrates light-weight PV into commercial good vehicles [39]. However, the addition of PV on the rooftop adds an expense and additional weight to the vehicle. It is also vulnerable to vandalism and crime due to the valuable PV panels [40]. Fig. 2 is a look-up figure to demonstrate the conditions under which each technology is suitable for (a) motorbike taxis and (b) minibus taxis. Separate figures for the two modalities are necessary due to different energy consumption per kilometre (kWh/km) and different charging powers: 3.5 kW for a motorbike and 11 kW for a minibus. Further details can be found in the appendicies.
The figure shows that vehicles which travel longer distances each day, and do not have sufficient time plugged in during daylight hours, may benefit from the adoption of a battery swap model. In some circumstances minibuses with on-board PV may benefit from a slight reduction in plug-in hours for charging. To understand the financial implications, for minibuses, on-board PV appears to be favourable when compared with a battery swap system, based on a calculation assuming a 2 kW PV array which costs US$2600 [41], compared to an additional 60 kWh battery pack which costs US$9360 [42]. However, sufficient space is necessary on the vehicle.
From this example, it is clear that there is no silver bullet. Technology choice depends significantly on driving patterns, and until mobility patterns are well recorded, it is challenging to determine which technology will be most suitable. This results in challenges for EV charging infrastructure planning and efforts must be made to gather and make available the required data [6].

Conclusion
In conclusion, we challenge the perception that EVs in SSA are an optimist's fantasy. Despite the obvious barriers of an unreliable electricity system and a lack of capital, we argue that EVs could offer benefits to governments, electricity systems, and paratransit owneroperators. The key to realising these benefits is to design EV systems which are context-specific and differ from existing HIC approaches.
If this is achieved, the majority of EVs in SSA will not take the form of the HIC private car. Instead, they will correspond to the modes of transport common in SSA such as the minibus or motorbike. Moreover, the vehicles and their charging infrastructure will be designed to support the marriage of the two previously siloed sectors: electricity and transport. This Viewpoint has highlighted how EVs could be good for SSA, providing benefits such as vehicle emission reductions of over 90%, decreased petroleum subsidies which are currently nearly US$200 per capita in South Africa, a flexible load to support the electricity network which could be worth up to US$14 billion in revenue per annum, cheaper vehicle operating costs of up to US$0.15 per kilometre, as well as a potential route to clean generation investment. These are summarised in Fig. 3.
All of these benefits hinge on understanding SSA transport and electricity systems in their own right, and not shoehorning inappropriate HIC solutions into SSA systems. Context-appropriate technologies and their associated business models need to be developed, be it for new EVs or retrofit options, such as battery swap, plug-in charging with colocated PV, and on-board PV.

Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. in this paper do not necessarily reflect the UK government's official policies.

A. Maps
The maps in Fig. 1 were generated using the existing electricity fuel mix in each country in 2019 [43], alongside standard emissions intensity values for each fuel [44]. Vehicle efficiencies of 0.31 kWh/km [45] and 20 mpg [46] were used, which are representative of older inefficient vehicles. A 90% EV charging efficiency was assumed, similar to those observed in home charging points [47].

B. Estimated electricity providers revenue potential
Estimated electricity providers revenue potential is calculated considering that transport demands 69 Mtoe per annum in SSA, equivalent to 800 TWh of energy per annum and that non-road transport is extremely low [2]. As EVs can be up to four times more efficient than an ICE, a transition of all vehicles to electric could result in a transport related electricity demand of 200 TWh per annum. Given that the average electricity price in SSA is US$0.14/kWh, this equates to a market value of up to US$28 billion. As a complete transition is extremely unlikely in the near future, we present the value for half the vehicles electrifying, equating to US$14 billion.

C. Owner-operator annual cost saving
The owner-operator annual cost saving is calculated using a saving of US$0.15/km, from Fig. 1(c) and assuming the vehicle covers 100 km/ day, five days a week, which is reflective of paratransit vehicle operation.

D. Look-up figure
The look-up figures in Fig. 2 were generated using the following assumptions. Energy consumption was taken to be 0.12 kWh/km for boda-bodas and 0.50 kWh/km for minibus taxis [34]. Battery capacities of the boda-boda and minibus were 20 kWh and 60 kWh, respectively [34]. The charging powers were taken to be the standard 3.5 kW for a boda-boda and 11 kW for a minibus (which is conservative, so as to minimise negative impact on the power network). The onboard solar PV was assumed to extend the vehicle range by 20%, instead of the 31% quoted by Kim et al. [38].