NOTE: This dataset has been retired and marked as historical-only. Weekly rates of COVID-19 cases, hospitalizations, and deaths among people living in Chicago by vaccination status and age. Rates for fully vaccinated and unvaccinated begin the week ending April 3, 2021 when COVID-19 vaccines became widely available in Chicago. Rates for boosted begin the week ending October 23, 2021 after booster shots were recommended by the Centers for Disease Control and Prevention (CDC) for adults 65+ years old and adults in certain populations and high risk occupational and institutional settings who received Pfizer or Moderna for their primary series or anyone who received the Johnson & Johnson vaccine. Chicago residency is based on home address, as reported in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE) and Illinois National Electronic Disease Surveillance System (I-NEDSS). Outcomes: • Cases: People with a positive molecular (PCR) or antigen COVID-19 test result from an FDA-authorized COVID-19 test that was reported into I-NEDSS. A person can become re-infected with SARS-CoV-2 over time and so may be counted more than once in this dataset. Cases are counted by week the test specimen was collected. • Hospitalizations: COVID-19 cases who are hospitalized due to a documented COVID-19 related illness or who are admitted for any reason within 14 days of a positive SARS-CoV-2 test. Hospitalizations are counted by week of hospital admission. • Deaths: COVID-19 cases who died from COVID-19-related health complications as determined by vital records or a public health investigation. Deaths are counted by week of death. Vaccination status: • Fully vaccinated: Completion of primary series of a U.S. Food and Drug Administration (FDA)-authorized or approved COVID-19 vaccine at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Boosted: Fully vaccinated with an additional or booster dose of any FDA-authorized or approved COVID-19 vaccine received at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Unvaccinated: No evidence of having received a dose of an FDA-authorized or approved vaccine prior to a positive test. CLARIFYING NOTE: Those who started but did not complete all recommended doses of an FDA-authorized or approved vaccine prior to a positive test (i.e., partially vaccinated) are excluded from this dataset. Incidence rates for fully vaccinated but not boosted people (Vaccinated columns) are calculated as total fully vaccinated but not boosted with outcome divided by cumulative fully vaccinated but not boosted at the end of each week. Incidence rates for boosted (Boosted columns) are calculated as total boosted with outcome divided by cumulative boosted at the end of each week. Incidence rates for unvaccinated (Unvaccinated columns) are calculated as total unvaccinated with outcome divided by total population minus cumulative boosted, fully, and partially vaccinated at the end of each week. All rates are multiplied by 100,000. Incidence rate ratios (IRRs) are calculated by dividing the weekly incidence rates among unvaccinated people by those among fully vaccinated but not boosted and boosted people. Overall age-adjusted incidence rates and IRRs are standardized using the 2000 U.S. Census standard population. Population totals are from U.S. Census Bureau American Community Survey 1-year estimates for 2019. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. This dataset reflects data known to CDPH at the time when the dataset is updated each week. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. For all datasets related to COVID-19, see https://data.cityofchic

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

Following Edward Jenner's development of the smallpox vaccine in 1796, the death rate due to smallpox in England and Wales dropped significantly. Although Jenner's work was published in 1797, it would take over half a century for the British government to make vaccination compulsory for all infants. Between 1847 and 1853, when vaccination was optional, children under the age of five years had, by far, the largest number of deaths; the total death rate was 1.6 thousand deaths per million people, which was more than five times the overall death rate due to smallpox. When compulsory vaccination was introduced, this helped bring the smallpox death rate in this age group down by over fifty percent between 1854 and 1871. When compulsory vaccination was enforced with penalties in the wake of the Great Pandemic of the 1870s, the smallpox death rate among children under the age of five dropped to approximately fifteen percent of its optional vaccination level. Increase among adults Along with the youngest age group, children aged five to ten years also saw their death rates decrease by roughly two thirds, and the death rate among those aged ten to 15 declined by just under one third during this time. It was among adults, aged above 15 years, where the introduction of mandatory vaccination had an adverse effect on their death rates; increasing by fifty percent among young adults, and almost doubling among those aged 25 to 45. The reason for this was because, contrary to Jenner's theory, vaccination did not guarantee lifelong protection, and immunization gradually wore off making vaccinated people susceptible to the virus again in adulthood. There was some decline in the smallpox death rates among adults throughout the 1870s and 1880s, as revaccination became more common, and the enforced vaccination of children prevented smallpox from spreading as rapidly as in the pre-vaccination era. Overall trends While the introduction of mandatory vaccination saw the number of smallpox deaths increase for age groups above 15 years, the overall rate among all ages decreased, due to the huge drop in deaths among infants and children. The smallpox death rate dropped by over one quarter when compulsory vaccination was introduced, and it then fell to just over one third of it's optional-vaccination level when these measures were enforced. The development of the smallpox vaccine and the implementation of mandatory vaccination led to the eradication of the disease in Britain by 1934, and contributed greatly to the demographic developments of the twentieth century, such as the declines in fertility rate and birth rate, and the increase in life expectancy.

In 1919, there were almost 13 deaths from measles per 100,000 population in the United States. However, this rate had dropped to zero by the year 2021. In early 2025, an outbreak of measles in Texas resulted in the death of a child. This was the first measles death in the United States since 2015. Measles is a highly contagious disease, that is especially dangerous for children. However, vaccines have significantly decreased the rate of cases and deaths in the United States.

Depending on the reach and level of vaccination within Europe's various states in the 1870s, smallpox had a varied impact on various age groups. For infants below the age of one year, smallpox was responsible for between 15 and 30 percent of all deaths in the given regions, as many of these babies had not yet been vaccinated and were at a high risk of succumbing to the virus. In states where the vaccination of infants was not compulsory, such as the Netherlands, Berlin (Prussia) and Leipzig (Saxony), the share of deaths due to smallpox among young children remained high, while it was relatively low in Hesse and Scotland, who had introduced mandatory vaccination in 1815 and 1864 respectively. Great Pandemic highlights the need for revaccination As Hesse had been vaccinating on a large scale for generations, the share of smallpox deaths was relatively low among young people; however, between 1870 and 1872, over half of all deaths among those aged 30 to 60 years were due to smallpox. The reason for this was because smallpox vaccination in infancy did not guarantee lifelong protection, therefore immunity often wore off in adulthood. In the 1830s and 1840s, several German armies started to vaccinate new recruits regardless of whether they had been vaccinated in infancy or not; when scientists compared the smallpox death rates in the army with that of the civilian population during this pandemic, they noticed that it was much lower in the army, due to these revaccination policies. This discovery helped many scientists in Europe recognize the need for revaccination, which greatly contributed to the eradication of the disease across most of Europe in the early twentieth century.

Global Covid-19 Data

Global Covid-19 data on cases, deaths, vaccinations, and more

By Valtteri Kurkela [source]

About this dataset

The dataset is constantly updated and synced hourly to ensure up-to-date information. With over several columns available for analysis and exploration purposes, users can extract valuable insights from this extensive dataset.

Some of the key metrics covered in the dataset include:

1. Vaccinations: The dataset covers total vaccinations administered worldwide as well as breakdowns of people vaccinated per hundred people and fully vaccinated individuals per hundred people.

2. Testing & Positivity: Information on total tests conducted along with new tests conducted per thousand people is provided. Additionally, details on positive rate (percentage of positive Covid-19 tests out of all conducted) are included.

3. Hospital & ICU: Data on ICU patients and hospital patients are available along with corresponding figures normalized per million people. Weekly admissions to intensive care units and hospitals are also provided.

4. Confirmed Cases: The number of confirmed Covid-19 cases globally is captured in both absolute numbers as well as normalized values representing cases per million people.

5.Confirmed Deaths: Total confirmed deaths due to Covid-19 worldwide are provided with figures adjusted for population size (total deaths per million).

6.Reproduction Rate: The estimated reproduction rate (R) indicates the contagiousness of the virus within a particular country or region.

7.Policy Responses: Besides healthcare-related metrics, this comprehensive dataset includes policy responses implemented by countries or regions such as lockdown measures or travel restrictions.

8.Other Variables of InterestThe data encompasses various socioeconomic factors that may influence Covid-19 outcomes including population density,membership in a continent,gross domestic product(GDP)per capita;

For demographic factors: -Age Structure : percentage populations aged 65 and older,aged (70)older,median age -Gender-specific factors: Percentage of female smokers -Lifestyle-related factors: Diabetes prevalence rate and extreme poverty rate

1. Excess Mortality: The dataset further provides insights into excess mortality rates, indicating the percentage increase in deaths above the expected number based on historical data.

The dataset consists of numerous columns providing specific information for analysis, such as ISO code for countries/regions, location names,and units of measurement for different parameters.

Overall,this dataset serves as a valuable resource for researchers, analysts, and policymakers seeking to explore various aspects related to Covid-19

How to use the dataset

Introduction:

• Understanding the Basic Structure:

  • The dataset consists of various columns containing different data related to vaccinations, testing, hospitalization, cases, deaths, policy responses, and other key variables.
  • Each row represents data for a specific country or region at a certain point in time.

• Selecting Desired Columns:

  • Identify the specific columns that are relevant to your analysis or research needs.
  • Some important columns include population, total cases, total deaths, new cases per million people, and vaccination-related metrics.

• Filtering Data:

  • Use filters based on specific conditions such as date ranges or continents to focus on relevant subsets of data.
  • This can help you analyze trends over time or compare data between different regions.

• Analyzing Vaccination Metrics:

  • Explore variables like total_vaccinations, people_vaccinated, and people_fully_vaccinated to assess vaccination coverage in different countries.
  • Calculate metrics such as people_vaccinated_per_hundred or total_boosters_per_hundred for standardized comparisons across populations.

• Investigating Testing Information:

  • Examine columns such as total_tests, new_tests, and tests_per_case to understand testing efforts in various countries.
  • Calculate rates like tests_per_case to assess testing efficiency or identify changes in testing strategies over time.

• Exploring Hospitalization and ICU Data:

  • Analyze variables like hosp_patients, icu_patients, and hospital_beds_per_thousand to understand healthcare systems' strain.
  • Calculate rates like icu_patients_per_million or hosp_patients_per_million for cross-country comparisons.

• Assessing Covid-19 Cases and Deaths:

  • Analyze variables like total_cases, new_ca...

In nineteenth century Belgium, smallpox vaccination was available but was never made compulsory. For this reason, the number of deaths due to smallpox fluctuated regularly (although data before 1864 is scarce*), and the Great Pandemic of the 1870s caused the number of smallpox deaths in Belgium to skyrocket to 4.2 thousand per million people in 1871. Several sources suggest that smallpox had a similar impact in the Netherlands throughout the early and mid-1800s, however the Netherlands introduced mandatory vaccination for all children who were to be enrolled in school in 1873, and following the Great Pandemic the Netherlands' death rate was much lower than that of Belgium. The last natural case of smallpox was recorded in the Netherlands in 1900 (making it the fourth country in the world to eradicate the disease on a national level), while the last endemic case of smallpox in Belgium occurred in 1926. Data for Italy and Hungary is also scarce throughout the century, however Hungary introduced mandatory vaccination and revaccination in 1887, while Italy did the same in 1888; over the next decade we can see that the average number of smallpox deaths in these countries decreased greatly, and endemic cases of smallpox were eliminated in Hungary in 1923, and in 1947 in Italy.

In human history, smallpox has been one of the most widespread and lethal diseases to occur in nature, taking hundreds of millions of lives across the globe before it was successfully eradicated in the twentieth century. Although an effective smallpox vaccine was first developed in England in 1796, it would take over a century for the vaccine to be understood and implemented across Europe. While the vaccine was discovered in England, it was in Germany where the practice of vaccination first took off on a large scale, and where the importance of revaccination was discovered. Bavaria leads in vaccination development The state of Bavaria was the first in Germany (and second in the world, after Iceland) to introduce mandatory smallpox vaccination for newborns. This was reflected in them generally having the lowest number of smallpox deaths in Europe in the mid-1800s. Before the vaccination era, infants and children were generally the most at risk of dying from smallpox infection; vaccination caused these death rates to plummet, however it then presented microbiologists with a new challenge. As the century progressed, the smallpox death rate among young adults increased and it became apparent that vaccination in infancy would not last until adulthood, thus the need for revaccination emerged, with Bavaria again at the forefront. The German Vaccination Law of 1874 It was during the great pandemic of the 1870s The German Vaccination Law of April 8, 1874 was passed; where all children under the age of two, and any unvaccinated child under the age of twelve had to be vaccinated by law. From this year we can see a sharp decrease in the death rate due to smallpox, where it remains consistently low for the remainder of the century. The introduction of this law brought the smallpox death rates in all German states in line with those of Bavaria, with the death rate in Württemberg dropping even below that of Bavaria. In contrast to Germany, mandatory smallpox vaccination was never introduced in Austria, and we can see that the death rate due to smallpox in Austria remained much higher than in Germany for the remainder of the century.

The previous history concerning hospitalization due to flu infection, receiving a flu vaccination, and frequency of vaccination (total number = 611, ever vaccinated = 267).

BackgroundLarge quantities of smallpox vaccine have been stockpiled to protect entire nations against a possible reintroduction of smallpox. Planning for an appropriate use of these stockpiled vaccines in response to a smallpox outbreak requires a rational assessment of the risks of vaccination-related adverse events, compared to the risk of contracting an infection. Although considerable effort has been made to understand the dynamics of smallpox transmission in modern societies, little attention has been paid to estimating the frequency of adverse events due to smallpox vaccination. Studies exploring the consequences of smallpox vaccination strategies have commonly used a frequency of approximately one death per million vaccinations, which is based on a study of vaccination with the New York City Board of Health (NYCBH) strain of vaccinia virus. However, a multitude of historical studies of smallpox vaccination with other vaccinia strains suggest that there are strain-related differences in the frequency of adverse events after vaccination. Because many countries have stockpiled vaccine based on the Lister strain of vaccinia virus, a quantitative evaluation of the adverse effects of such vaccines is essential for emergency response planning. We conducted a systematic review and statistical analysis of historical data concerning vaccination against smallpox with different strains of vaccinia virus. Methods and FindingsWe analyzed historical vaccination data extracted from the literature. We extracted data on the frequency of postvaccinal encephalitis and death with respect to vaccinia strain and age of vaccinees. Using a hierarchical Bayesian approach for meta-analysis, we estimated the expected frequencies of postvaccinal encephalitis and death with respect to age at vaccination for smallpox vaccines based on the NYCBH and Lister vaccinia strains. We found large heterogeneity between findings from different studies and a time-period effect that showed decreasing incidences of adverse events over several decades. To estimate death rates, we then restricted our analysis to more-recent studies. We estimated that vaccination with the NYCBH strain leads to an average of 1.4 deaths per million vaccinations (95% credible interval, 0–6) and that vaccination with Lister vaccine leads to an average of 8.4 deaths per million vaccinations (95% credible interval, 0–31). We combined age-dependent estimates of the frequency of death after vaccination and revaccination with demographic data to obtain estimates of the expected number of deaths in present societies due to vaccination with the NYCBH and Lister vaccinia strains. ConclusionsPrevious analyses of smallpox vaccination policies, which rely on the commonly assumed value of one death per million vaccinations, may give serious underestimates of the number of deaths resulting from vaccination. Moreover, because there are large, strain-dependent differences in the frequency of adverse events due to smallpox vaccination, it is difficult to extrapolate from predictions for the NYCBH-derived vaccines (stockpiled in countries such as the US) to predictions for the Lister-derived vaccines (stockpiled in countries such as Germany). In planning for an effective response to a possible smallpox outbreak, public-health decision makers should reconsider their strategies of when to opt for ring vaccination and when to opt for mass vaccination.

Factors associated with the Covid-19 mortality rate (cumulative data: Feb 2020 –Dec 2022).

COVID-19 has caused about 580 million cases and 6.4 million deaths worldwide by August 8th, 2022, including 8.7 million cases (173,063 deaths) in Africa. East Africa reported 1.39 million cases on July, 2022. Tanzania confirmed 37,865 cases and 841 deaths by 8th August 2022. Although billions of vaccine doses administered globally, just 17.6% of Tanzanians are fully vaccinated. Symptomatic pregnant women face a mortality risk that is 70% higher than in non-pregnant women.. Therefore, this study aimed at assessing knowledge, attitude, and acceptance of COVID-19 vaccine among pregnant women in the Mbeya region. A descriptive cross-sectional study was conducted in the Obstetrics and Gynecology department of MZRH. Three scores were calculated for participants’ knowledge, attitude, and acceptance to COVID-19 vaccination. These scores were compared to many sample factors using binary logistic regression and the chi-square test. The study recruited 233 participants. Most participants (31.3%) relied on social media for Covid-19 vaccine information. Poor Covid-19 vaccine knowledge (71.2%), negative attitudes (76.8%), and low acceptance rate (38.6%) were observed. Multivariate analysis showed that greater acceptance was positively associated with having a chronic illness (AOR = 3.21, CI 1.448-7.123, P = 0.004), stronger vaccine attitudes (AOR = 1.26, CI 1.149-1.368, P = 0.015), better vaccine knowledge (AOR = 2.70, CI 2.587-2.810, P = 0.005), and prior vaccination history (AOR = 0.13, CI 0.068-0.183, P = 0.000). Conversely, preference for natural immunity (AOR = 0.42, CI 0.341-0.498, P = 0.018), and not yet being vaccinated (AOR = 0.67, CI 0.594-0.755, P = 0.000) were all linked to lower acceptance. Pregnant women exhibited low knowledge, attitude, and acceptance to COVID-19 vaccines. Misinformation about the COVID-19 vaccine causes pause. Education on COVID-19 vaccination is needed to enhance vaccine uptake among pregnant women. This group must comprehend COVID-19 immunization importance, safety, and efficacy.

Multivariate analysis showing acceptance of COVID-19 vaccine.

The Great Smallpox Pandemic of 1870 to 1875 was the last major smallpox epidemic to reach pandemic level across Europe. The outbreak has its origins in the Franco-Prussian War of 1870 to 1871, where unvaccinated French prisoners of war infected the German civilian population, before the virus then spread to all corners of Europe. The death rates peaked in different years for individual countries; with the highest numbers recorded in 1871 for the German states, Belgium and the Netherlands, while death rates peaked in Austria, Scotland and Sweden in later years (the states that peaked in 1871 were closer in proximity to the frontlines of the Franco-Prussian War). Impact of compulsory vaccination The average number of deaths per million people was much higher in countries without compulsory vaccination, ranging from 953 to 1,360 in the samples given here. In comparison to this, the countries with compulsory vaccination barely reached these numbers in the years when the epidemic was at its worst, and their annual averages ranged between 314 and 361 deaths per million people during the six years shown here. Impact of the Great Pandemic Following the surge in smallpox deaths caused by the pandemic, many of the countries listed here introduced mandatory vaccination, or introduced penalties for parents who did not vaccinate their children. Germany and the Netherlands** did this in 1874, while Britain and Sweden enforced their vaccination laws with stricter penalties in 1871 and 1880 respectively. Perhaps surprisingly, Austria and Belgium, the two countries with the highest average death rate shown here, never introduced mandatory smallpox vaccination.

National and provincial age standardized mortality rate in Iran (per 100,000) for both sexes and the percentage of change (Δ).

Although vaccination was discovered in England in 1796, the practice was not made compulsory until 1853 in England and Wales, and 1864 in Scotland. For this reason, the number of smallpox deaths per million people fluctuated from year to year, often doubling or tripling from one year to the next, before the death rate for both countries settled in the late 1960s. The Great Pandemic of the 1870s, which was the last major smallpox pandemic in Europe, caused the number of smallpox deaths to soar once more, peaking at over 1,000 deaths per million people in England and Wales in 1871, and at over 820 deaths per million people in Scotland in 1872. During this pandemic, mandatory vaccination became enforced, where parents who did not vaccinate their children within the first three years of life were penalized with fines or imprisonment, and this helped the smallpox death rate to remain low and plateau in the final two decades of the nineteenth century; an estimated 11,000 of these penalties were handed out during the 1880s, which included 115 prison sentences for failure to vaccinate children. Smallpox cases in Britain were rare throughout the early twentieth century; not counting a lab accident in 1978 that infected two people (one of whom died), natural smallpox cases were eradicated in Britain in 1934.

In the eighteenth century, before vaccination was introduced to Sweden, smallpox epidemics were much more severe and regular than in the nineteenth century. Between 1774 and 1802, epidemics in Sweden peaked roughly every five years, with the toll reaching over seven thousand deaths per million people in some years. When vaccination was introduced to Sweden in the early 1800s, it greatly decreased the total number of smallpox deaths per million people, with the number never exceeding one thousand deaths per million people in any year after 1809. In actual numbers, there were roughly two thousand smallpox deaths per year in Sweden during the pre-vaccination era; optional vaccination helped bring this average down to 623 deaths between 1802 and 1811, while the number dropped to 176 between 1857 and 1866 when compulsory vaccination was introduced. Vaccination in Sweden became enforced in 1880, where parents were punished with fines or imprisonment for failing to immunize their child, and this helped bring the average number of smallpox deaths to just two deaths per year over the next two decades. Although there were some cases and fatalities recorded in the late 1890s, naturally occurring cases of smallpox were eliminated in Sweden in 1895, which made Sweden the second country in the world (after Iceland in 1872) to successfully eradicate the disease.

The development of vaccination by Edward Jenner in 1796 is seen by many as one of the most important and world-changing medical discoveries ever made. Throughout human history, smallpox was responsible for an untold and innumerable share of fatalities, with epidemics devastating countries (and even continents) in their wake; as of 1980, the World Health Organization declared smallpox to be eliminated in nature, making it the only human disease to have been successfully eradicated. If we look at the share of smallpox deaths in England over the nineteenth century, we can see the impact that vaccination had on society during this time. Decline in Britain Within this century, the number of people dying annually from smallpox dropped from 3,000 per million people in the 1700s, to just ten people per million in the 1890s (it is also worth noting that a smallpox pandemic swept across Britain between 1891 and 1893, which caused this number to be higher than it could have been). Mandatory vaccination was not introduced in England until 1853, but by this point the number of smallpox deaths per million people had already fallen to a fraction of its eighteenth century level, and compulsory vaccination reduced these numbers even further.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

Factors associated with vaccination rates (cumulative data: From January 2021 to December 2022).