key: cord-0734826-gta5w38w authors: Middelburg, Rutger A.; Rosendaal, Frits R. title: COVID-19: how to make between-country comparisons date: 2020-05-26 journal: Int J Infect Dis DOI: 10.1016/j.ijid.2020.05.066 sha: 725f88f863cfb160f89c5127ab9ed59bd9ea5a5b doc_id: 734826 cord_uid: gta5w38w BACKGROUND: Different countries have adopted different containment and testing strategies for SARS-CoV-2. The difference in testing makes it difficult to compare the effect of different containment strategies. We propose methods to allow a direct comparison and we present the results of this comparison. DESIGN: Publicly available data on numbers of reported COVID-19 related deaths between January 1(st) and April 17(th) 2020 were compared between countries. RESULTS: The numbers of cases or deaths per 100,000 inhabitants give severely biased comparisons between countries. Only the number of deaths expressed as a percentage of the number of deaths on day 25 after the first reported COVID-19 related death allows a direct comparison between countries. From this comparison we observed clear differences between countries, associated with the timing of the implementation of containment measures. CONCLUSIONS: Comparisons between countries are only possible when simultaneously taking into account that the virus did not arrive in all countries simultaneously, absolute numbers are incomparable due to different population sizes, rates per 100,000 of the population are incomparable because not all countries are affected homogeneously, susceptibility to death by COVID-19 can differ between populations, and a death will only be reported as a COVID-19 related death if the patient was diagnosed with SARS-CoV-2 infection. With our methods, we accounted for all these factors and established an unbiased direct comparison between countries. This comparison confirms that early adoption of containment strategies is key in flattening the curve of the epidemic. Since the start of the outbreak of SARS-CoV-2 in December 2019, in the Hubei province in China, the virus has quickly spread across the world. [1] [2] [3] As the virus spread, so did the COVID-19 disease that it causes. To curb the surge in COVID-19 related mortality, different governments enforced different measures for the containment of the epidemic. [4, 5] Comparing numbers of cases between countries is difficult, due to vast differences in testing policies. Now, as the epidemic claims more lives worldwide, the accumulation of mortality can be compared between countries, [6, 7] to obtain some insight into the effectiveness of the different containment measures. However, even for mortality, a direct comparison of crude rates between countries will be biased. Here, we propose methods to enable a comparison and present the results of this comparison. Reported numbers of cases and deaths per country were obtained from the European Union Open Data Portal, where data on worldwide numbers of reported cases and numbers of reported deaths, for the COVID-19 epidemic are updated daily. [6] Numbers of reported cases and deaths between January 1 st and April 17 th 2020 were compared between countries. The comparability of data between countries was increased in two distinct ways. First, the start of the epidemic was synchronized between countries, by using the date of the first reported COVID-19 case or COVID-19 related death as the index date. Second, the size and susceptibility of the population, and the probability of a COVID-19 case or a COVID-19 related death being reported as such, were all corrected for in a single procedure. All cumulative numbers of cases or deaths were normalized to a reference number. As a reference we took the cumulative number of cases or deaths at day 25 of the synchronized epidemic (i.e. day 25 after the index date for each country). We chose day 25 as the reference day because, in most countries, by day 25 after the first case or death, the epidemic has stably established itself and the number of cases or deaths has increased to a level where random fluctuations are reduced to an acceptable level. To assess the potential influence of choosing day 25 as a reference, sensitivity analyses were performed repeating all analyses, while taking days 20 and 30 as the references. After synchronizing countries by the date of the first death in each country, cumulative numbers of deaths were expressed as percentages of the cumulative number of deaths on day 25, for each country. Resulting percentages were expressed in graphs, plotted against synchronized time. Temporal trends in cumulative numbers of deaths were compared to those for China, where the epidemic started, and where the temporal trends have therefore developed the farthest. For comparison to China, countries were divided into three categories. First, countries with a policy similar to that of China. These are the European countries, where governments waited for the epidemic to establish itself, but not for substantial numbers of COVID-19 related deaths to occur, before taking preventive measures. Germany, Italy, the Netherlands, Spain, and Sweden (alphabetic order) were used as examples, but graph shapes for other European countries were rather similar. Second, in South Korea, strict preventive measures were put into place even before the virus spread substantially in the population. Third, a comparison was made with the United States of America (USA), where preventive measures were not put into place until large numbers of deaths had already occurred. As shown in figure 1 , the temporal development of the epidemic appears very different between different countries in panels A through C, but not in panel D. When comparing the number of cases To appreciate our results, it is important to note that data from different countries are not directly comparable, for at least five distinct reasons. First, the virus did not arrive in all countries simultaneously, causing a desynchronized development of the epidemic in different countries. Second, absolute numbers are incomparable due to different population sizes. Third, rates per 100,000 of the population are incomparable, because not all countries are affected homogeneously. Especially in the larger countries, like China and the United States, epidemics can be (temporarily) focused on a localized level. For example, in China, the province of Hubei was severely affected, while the rest of the country was not. Therefore, correction for the total size of the Chinese population would not provide a representative figure. Of particular note, in panels A and B of figure 1 , the numbers of cases and deaths in China disappear almost completely, due to this false inflation of the denominator. Fourth, susceptibility to death by COVID-19 can differ between populations, depending on the demographic composition of a country's population. For example, in Italy, older people are known to be relatively overrepresented in the population, and to be more likely to be in a single household with relatives from a younger generation, causing increased numbers of elderly to be infected and therefore relatively more COVID-19 mortality. Fifth, a death during the COVID-19 epidemic will only be reported as a COVID-19 related death if the patient was diagnosed with SARS-CoV-2 infection. Therefore, differences in testing policy and guidelines for clinical diagnosis (i.e. in the absence of laboratory testing), will also cause differences in estimated numbers of COVID-19 related deaths. The first problem was addressed by choosing an appropriate index date for each country and setting this date to day 1, for the start of the epidemic in that country. As an index date, we choose the date of the first reported COVID-19 related case or death in each country, depending on whether cases or deaths were being synchronized. Admitted, chance processes play a role here, causing some uncertainty in the determination of the index date. This was especially clear for the date of the index case ( figure 1 panels A and C) . Synchronization of the development of deaths by the date of the first death was much better ( figure 1 panels B and D) . The remaining four problems all pertain to the size and the susceptibility of the population, or the probability of a COVID-19 case or COVID-19 related death being reported as such. Adequately control for all factors influencing these problems is a practical impossibility. Therefore, we choose to normalize the cumulative number of deaths, by a reference number of deaths. The number of actually reported COVID-19 related deaths is clearly a direct function of the size and susceptibility of the population and the probability of a COVID-19 J o u r n a l P r e -p r o o f related death being reported as such. Therefore, taking the reported number of COVID-19 related deaths on a synchronized reference date as a standard will correct results for all these factors simultaneously. In conclusion, although the future development of the epidemic remains difficult to predict accurately, due to changing containment policies, changing seasonal influences, [8] and the possibility of a depletion of susceptibles, or the development of herd immunity, [9, 10] current data suggest the USA should expect an explosive increase in cumulative mortality due to COVID-19, with containment policies still lagging behind, while most European countries seem well on the way to containing the epidemic. RAM conceptualised, designed, and executed the research, wrote the manuscript, and affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned have been explained. FRR conceptualised the research and revised the manuscript. ☒ 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. None of the authors report any competing interest relevant to this paper. There was no funding for this research. Since only publicly available data was used, no ethical approval was required. Current Status of Epidemiology, Diagnosis, Therapeutics, and Vaccines for Novel Coronavirus Disease 2019 (COVID-19) SARS-CoV-2 (COVID-19) by the numbers Covid-19: hospitals brace for disaster as US surpasses China in number of cases The First 75 Days of Novel Coronavirus (SARS-CoV-2) Outbreak: Recent Advances, Prevention, and Treatment An international comparison of the second derivative of COVID-19 deaths after implementation of social distancing measures Open Data Portal: COVID-19 cases worldwide Forecasting the novel coronavirus COVID-19 Potential impact of seasonal forcing on a SARS-CoV-2 pandemic Herd immunity -estimating the level required to halt the COVID-19 epidemics in affected countries An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov) We wish to thank all clinicians worldwide, who in the difficult situation they find themselves in, trying to save as many lives as possible during this dramatic epidemic, have taken the time to report COVID-19 related deaths, to help science understand the epidemic better. Further, we thank Dr