We develop a simple 3-dimensional iterative map model to forecast the global spread of the coronavirus disease. Our model contains only one fitting parameter , which we determine from the data supplied by the world URLanisation for the total number of cases and new cases each day. We find that our model provides a surprisingly good fit to the currently-available data . It predicts that the disease will run its full course over six to seven months , starting from the date on which the world URLanisation provided the first ' Situation report' (21 January 2020 - day 1). The disease may be expected to infect approximately 24 \% of the global population, i.e. about 1.83 billion people, taking approximately 86 million lives. Unless drastic new interventions become possible , the global number of new cases is predicted to peak on day 129 (about the middle of May 2020), with an estimated 65 million new cases per day. Since our simple model fits the available global data so well, we suggest that the measures being taken so far to contain the pandemic may be ineffective in curbing the global  spread of the virus . As such, the efficacy of these measures should be more carefully weighed against their impact on the world economy.
We develop a simple 3-dimensional iterative map model to forecast the global spread of the coronavirus disease. Our model contains at most two fitting parameters , which we determine from the data supplied by the world URLanisation for the total number of cases and new cases each day. We find that our model provides a surprisingly good fit to the currently-available data , which exhibits a cross-over from exponential to power-law growth, as lock-down measures begin to take effect. Before these measures, our model predicts exponential growth from day 30 to 69 , starting from the date on which the world URLanisation provided the first ` Situation report' (21 January 2020 - day 1). Based on this initial data the disease may be expected to infect approximately 23 \% of the global population, i.e. about 1.76 billion people, taking approximately 83 million lives. Under this scenario , the global number of new cases is predicted to peak on day 133 (about the middle of May 2020), with an estimated 60 million new cases per day. If current lock-down measures can be maintained, our model predicts power law growth from day 69 onward. Such growth is comparatively slow and would have to continue for several decades before a sufficient number of people (at least 23\% of the global population) have developed immunity to the disease through being infected. Lock-down measures appear to be very effective in postponing the unimaginably large peak in the daily number of new cases that would occur in the absence of any interventions. However, should these measure be relaxed, the spread of the disease will most likely revert back to its original exponential growth pattern . As such, the duration and severity of the lock-down measures should be carefully timed against their potentially devastating impact on the world economy.
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Since our simple model fits the available global data so well, we suggest that the measures being taken so far to contain the pandemic may be ineffective in curbing the
If current lock-down measures can be maintained, our model predicts power law growth from day 69 onward. Such growth is comparatively slow and would have to continue for several decades before a sufficient number of people (at least 23\% of the
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population) have developed immunity to the disease through being infected. Lock-down measures appear to be very effective in postponing the unimaginably large peak in the daily number of new cases that would occur in the absence of any interventions. However, should these measure be relaxed, the
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