A seven-day cycle in COVID-19 infection, hospitalization, and mortality rates: Do weekend social interactions kill susceptible people?

Abstract

AbstractSeven-day cycles in numbers of COVID-19 new-cases and deaths are markedly evident in most public databases (e.g. Worldometer, ECDC), but it is unclear whether they reflect systematic artifacts of delays in information reporting/gathering, or have a more profound basis. To address this question we located 11 databases of US states that provide date- authenticated information (actual date of symptom onset and/or specimen collection, or actual hospitalization or death date) that reported more than 1,000 deaths each. Numbers of new cases showed a weekly cyclic pattern in 10 out of 11 states, commonly peaking on weekdays, 2-6 days after the weekend, corresponding with a reported median 5-day lag between infection and the manifestation of clinical symptoms. We postulate that this pattern emerges from interactions with different and/or extended social-circles during weekends, including increased inter-generational meetings, which in turn facilitate transfer of COVID-19 from younger people to older vulnerable individuals. Furthermore, we found weekly periodicity in hospitalizations in 2 out of 2 authenticated databases providing this information. Actual death date, which is more difficult to attribute to individual choice, and is expected to occur approximately 2-3 weeks following hospitalization, showed significant 7-day periodicity in 1 out of 11 states, and a trend in 2 additional states. If weekly peaks in new cases can be truncated by physical/social distancing, especially during weekends, the mortality of COVID-19 may be reduced, or at least hospitalization and mortality curves may be flattened.Significance StatementWe believe our findings are significant, as it appears that it is difficult for people to grasp an ambiguous “price” for visiting their friends and family, when they cannot be certain that they are not carrying and spreading the virus. Our findings could be used as an effective “tool” to demonstrate such a cost, clearly presented in terms of number of excessive infections. During these days of uncertainly, we believe it is fundamental to provide scientific facts that could illuminate this connection and make it tangible for the general. The amplitude of the cycles we describe here is such that many thousands of infections could be averted by carefully scrutinizing local policies, medical practice, and social norms.