Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

Aims and objectives: The pandemic of COVID-19 is evolving worldwide, and it is associated with high mortality and morbidity. There is a growing need to discuss the elements of a coordinated strategy to control the spread and mitigate the severity of COVID-19. H1N1 and Streptococcus pneumonia vaccines are available. The current analysis was performed to analyze the severity of COVID-19 and influenza (H1N1) vaccination in adults ≥ 65. Also, to correlate the lower respiratory tract infections (LRIs), and influenza attributable to the lower respiratory tract infections' incidence with Covid-19 mortality. Evolutionarily influenza is close in resemblance to SARS-CoV-2 viruses and shares some common epitopes and mechanisms.Methods: Recent influenza vaccination data of 34 countries from OECD and other publications were correlated with COVID-19 mortality from worldometer data. LRIs attributable to influenza and streptococcus pneumonia were correlated with COVID-19 mortality. Specifically, influenza-attributable LRI incidence data of various countries (n = 182) was correlated with COVID-19 death by linear regression and receiver operating characteristic (ROC) curve analyzes. In a logistic regression model, population density and influenza LRI incidence were correlated with COVID-19 mortality.Results: There is a correlation between COVID-19-related mortality, morbidity, and case incidence and the status of influenza vaccination, which appears protective. The tendency of correlation is increasingly highlighted as the pandemic is evolving. In countries where influenza immunization is less common, there is a correlation between LRIs and influenza attributable to LRI incidence and COVID-19 severity, which is beneficial. ROC curve showed an area under the curve of 0.86 (CI 0.78 to 0.944, P < 0.0001) to predict COVID-19 mortality >150/million and a decreasing trend of influenza LRI episodes. To predict COVID-19 mortality of >200/million population, the odds ratio for influenza incidence/100,000 was −1.86 (CI −2.75 to −0.96, P < 0.0001). To predict the parameter Covid-19 mortality/influenza LRI episodes*1000>1000, the influenza parameter had an odd's ratio of −3.83 (CI −5.98 to −1.67), and an AUC of 0.94.Conclusion: Influenza (H1N1) vaccination can be used as an interim measure to mitigate the severity of COVID-19 in the general population. In appropriate high-risk circumstances, Streptococcus pneumonia vaccination would also be an adjunct strategy, especially in countries with a lower incidence of LRIs.