The engines of SARS-CoV-2 spread
This is a frustrating editorial. The authors make a credible case that the majority of transmission occurs <i>inside households</i> (where we are doing little&#x2F;nothing to prevent spread), and that the probability of &quot;community transmission&quot; (where we are doing a lot, at great societal cost) is low...but they word it in a way that hides the impact of what they&#x27;re saying:<p><i>&quot;For SARS-CoV-2, studies suggest that ∼10% of cases cause 80% of infections (1). Overdispersion is characterized by a large number of people who infect no one, and most people who do transmit infect a low-to-moderate number of individuals.&quot;</i><p><i>&quot;overdispersion means that most infected individuals who enter a community will not transmit, so many introductions may occur before an epidemic takes hold; likewise, overdispersion also increases the probability of disease extinction as the epidemic recedes and fewer people are infected.&quot;</i><p><i>&quot;If transmission is highly overdispersed, broad and untargeted interventions may be less effective than expected, whereas interventions targeted at settings conducive to superspreading (such as mass gatherings and hospitals) may have an outsized effect.&quot;</i><p>They then make the argument that this pattern of transmission makes it unlikely for things like travel bans to have an effect:<p><i>&quot;Only a small number of such long-distance connections are needed to create a “small world” network in which only a few infection events can transmit the virus between any two individuals worldwide. This is one reason why early travel bans could not stop the global spread of SARS-CoV-2, although they may have slowed the pandemic.&quot;</i><p>Then they move on to the importance of preventing spread <i>in the household</i>, via relatively inexpensive interventions:<p><i>&quot;Moving from international to household scales, the burdens of interventions are shared by more people; there are few international travelers, but nearly everyone lives in households and communities. Measures to reduce household spread may appear particularly challenging, but because they directly affect so many, they need not be perfect. Household mask use and partitioning of home spaces, isolation or quarantine outside the home, and, in the future, household provision of preventive drugs could have large effects even if they offer only modest protection.&quot;</i><p>So overall, everything in this article draws a (IMHO convincing) conclusion that our interventions should be focused on <i>household transmission</i>. Then they go on to say that community transmission control measures must be <i>draconian</i> in order to be effective:<p><i>&quot;Conversely, control measures at larger spatial scales (for example, interregional) must be widely implemented and highly effective to contain the virus. Indeed, few nations have managed to curb infection without stay-at-home orders and business closures, particularly after community transmission is prevalent.&quot;</i><p>Unfortunately, they&#x27;ve worded this in a weird way, which makes it sounds like they&#x27;re <i>advocating</i> for such measures, when they&#x27;re actually doing the opposite; the article is fundamentally about how even if you miss <i>one transmission event</i>, it&#x27;s enough to keep the graph connected. So overall, this article is saying that we&#x27;re doing it wrong: we should be focused on the middle of the bell curve, where modest efforts can yield greater results, instead of spending huge amounts of money to unsuccessfully filter out infrequent, improbable events.<p>Said in a way that might be more intuitive for programmers, it&#x27;s similar to the expenses required to ensure system uptime. While it&#x27;s possible to obtain (e.g.) 95% uptime with very little effort, getting to 99% requires significantly greater costs (redundant servers, etc). Getting to 99.9% requires significantly <i>more</i> expense (e.g. datacenter redundancy, hot deploys, etc.), so on and so forth. Every additional fraction of a percent of bad stuff that you try to stop costs <i>orders of magnitude</i> more effort. The same thing applies here: it&#x27;s relatively inexpensive to ask people to do things <i>at home</i>, but shutting down all businesses and international travel is an incredibly expensive intervention, aimed at the tails of the distribution.