As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

As of May 2, 2023, the coronavirus disease (COVID-19) had been confirmed in almost every country and territory around the world. There had been roughly 687 million cases and 6.86 million deaths.

Vaccine approval in the United States The United States has recorded more coronavirus infections and deaths than any other country in the world. The regulatory agency in the country authorized three COVID-19 vaccines for emergency use. Both the Pfizer-BioNTech and Moderna vaccines were approved in December 2020, while the Johnson & Johnson vaccine was approved in February 2021. As of April 26, 2023, the number of COVID-19 vaccine doses administered in the U.S. had reached 675 million.

The difference between vaccines and antivirals Medications can help with the symptoms of viruses, but it is the role of the immune system to take care of them over time. However, the use of vaccines and antivirals can help the immune system in doing its job. The most tried and tested vaccine method is to inject an inactive or weakened form of a virus, encouraging the immune system to produce protective antibodies. The immune system keeps the virus in its memory, and if the real one appears, the body will recognize it and attack it more efficiently. Antivirals are designed to help target viruses, limiting their ability to reproduce and spread to other cells. They are used by patients who are already infected by a virus and can make the infection less severe.

United States recorded 16306656 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, United States reported 797346 Coronavirus Deaths. This dataset includes a chart with historical data for the United States Coronavirus Recovered.

According to data from McKinsey, ** percent of respondents from the United States were optimistic about their country's economic recovery following COVID-19. ** percent of American respondents were pessimistic.

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.Revisions added on 4/23/2020 are highlighted.Revisions added on 4/30/2020 are highlighted.Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Correction on 6/1/2020Methodology 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.Reasons for undertaking this work: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 15-30 days + 5% from past 31-56 days - total deaths.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 used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 14 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.Past five days is less than the past 14 days. This means a downward trend. This would be an

In New York City, around 46 percent of adults believed the city would not fully recovery from COVID-19 until there was a vaccine. This statistic shows the proportion of people in New York City who thought the city would fully recover from the COVID-19 pandemic by select times , as of September 2020.

Context

Covid-19 Data collected from various sources on the internet. This dataset has daily level information on the number of affected cases, deaths, and recovery from the 2019 novel coronavirus. Please note that this is time-series data and so the number of cases on any given day is the cumulative number.

Content

The dataset includes 28 files scrapped from various data sources mainly the John Hopkins GitHub repository, the ministry of health affairs India, worldometer, and Our World in Data website. The details of the files are as follows

• countries-aggregated.csv A simple and cleaned data with 5 columns with self-explanatory names. -covid-19-daily-tests-vs-daily-new-confirmed-cases-per-million.csv A time-series data of daily test conducted v/s daily new confirmed case per million. Entity column represents Country name while code represents ISO code of the country. -covid-contact-tracing.csv Data depicting government policies adopted in case of contact tracing. 0 -> No tracing, 1-> limited tracing, 2-> Comprehensive tracing. -covid-stringency-index.csv The nine metrics used to calculate the Stringency Index are school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. The index on any given day is calculated as the mean score of the nine metrics, each taking a value between 0 and 100. A higher score indicates a stricter response (i.e. 100 = strictest response). -covid-vaccination-doses-per-capita.csv A total number of vaccination doses administered per 100 people in the total population. This is counted as a single dose, and may not equal the total number of people vaccinated, depending on the specific dose regime (e.g. people receive multiple doses). -covid-vaccine-willingness-and-people-vaccinated-by-country.csv Survey who have not received a COVID vaccine and who are willing vs. unwilling vs. uncertain if they would get a vaccine this week if it was available to them. -covid_india.csv India specific data containing the total number of active cases, recovered and deaths statewide. -cumulative-deaths-and-cases-covid-19.csv A cumulative data containing death and daily confirmed cases in the world. -current-covid-patients-hospital.csv Time series data containing a count of covid patients hospitalized in a country -daily-tests-per-thousand-people-smoothed-7-day.csv Daily test conducted per 1000 people in a running week average. -face-covering-policies-covid.csv Countries are grouped into five categories: 1->No policy 2->Recommended 3->Required in some specified shared/public spaces outside the home with other people present, or some situations when social distancing not possible 4->Required in all shared/public spaces outside the home with other people present or all situations when social distancing not possible 5->Required outside the home at all times regardless of location or presence of other people -full-list-cumulative-total-tests-per-thousand-map.csv Full list of total tests conducted per 1000 people. -income-support-covid.csv Income support captures if the government is covering the salaries or providing direct cash payments, universal basic income, or similar, of people who lose their jobs or cannot work. 0->No income support, 1->covers less than 50% of lost salary, 2-> covers more than 50% of the lost salary. -internal-movement-covid.csv Showing government policies in restricting internal movements. Ranges from 0 to 2 where 2 represents the strictest. -international-travel-covid.csv Showing government policies in restricting international movements. Ranges from 0 to 2 where 2 represents the strictest. -people-fully-vaccinated-covid.csv Contains the count of fully vaccinated people in different countries. -people-vaccinated-covid.csv Contains the total count of vaccinated people in different countries. -positive-rate-daily-smoothed.csv Contains the positivity rate of various countries in a week running average. -public-gathering-rules-covid.csv Restrictions are given based on the size of public gatherings as follows: 0->No restrictions 1 ->Restrictions on very large gatherings (the limit is above 1000 people) 2 -> gatherings between 100-1000 people 3 -> gatherings between 10-100 people 4 -> gatherings of less than 10 people -school-closures-covid.csv School closure during Covid. -share-people-fully-vaccinated-covid.csv Share of people that are fully vaccinated. -stay-at-home-covid.csv Countries are grouped into four categories: 0->No measures 1->Recommended not to leave the house 2->Required to not leave the house with exceptions for daily exercise, grocery shopping, and ‘essent...

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COVID-19 Worldwide Daily Data

Daily global COVID-19 data for all countries, provided by Johns Hopkins University (JHU) Center for Systems Science and Engineering (CSSE). If you want to use the update version of the data, you can use our daily updated data with the help of api key by entering it via Altadata.

Overview

In this data product, you may find the latest and historical global daily data on the COVID-19 pandemic for all countries.

The COVID‑19 pandemic, also known as the coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID‑19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The outbreak was first identified in December 2019 in Wuhan, China. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March. As of 12 August 2020, more than 20.2 million cases of COVID‑19 have been reported in more than 188 countries and territories, resulting in more than 741,000 deaths; more than 12.5 million people have recovered.

The Johns Hopkins Coronavirus Resource Center is a continuously updated source of COVID-19 data and expert guidance. They aggregate and analyze the best data available on COVID-19 - including cases, as well as testing, contact tracing and vaccine efforts - to help the public, policymakers and healthcare professionals worldwide respond to the pandemic.

Methodology

• Cases and Death counts include confirmed and probable (where reported)
• Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state-level recovered cases are from COVID Tracking Project.
• Active cases = total cases - total recovered - total deaths
• Incidence Rate = cases per 100,000 persons
• Case-Fatality Ratio (%) = Number recorded deaths / Number cases
• Country Population represents 2019 projections by UN Population Division, integrated to the JHU CSSE's COVID-19 data by ALTADATA

Data Source

• Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)
• United Nations Population Division

Related Data Products

• COVID-19 US Daily Data
• OECD, EU28, G20 Life Expectancy and Mortality Indicators

Suggested Blog Posts

• Bayesian Thinking During the Pandemic
• Impact of COVID-19 on California Electricity Demand
• Keep Calm and Look At The Fundamentals
• Markets In The Corona Virus Crisis

Data Dictionary

• Reported Date (reported_date) : Covid-19 Report Date
• Country_Region (country_region) : Country, region or sovereignty name
• Population (population) : Country populations as per United Nations Population Division
• Confirmed Case (confirmed) : Confirmed cases include presumptive positive cases and probable cases
• Active cases (active) : Active cases = total confirmed - total recovered - total deaths
• Deaths (deaths) : Death cases counts
• Recovered (recovered) : Recovered cases counts
• Mortality Rate (mortality_rate) : Number of recorded deaths * 100 / Number of confirmed cases
• Incident Rate (incident_rate) : Confirmed cases per 100,000 persons

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ALTADATA is a curated data marketplace where our subscribers and our data partners can easily exchange ready-to-analyze datasets and create insights with EPO, our visual data analytics platform.

COVID-19 US Daily Data

State level daily COVID-19 data for United States, provided by Johns Hopkins University (JHU) Center for Systems Science and Engineering (CSSE). If you want to use the updated version of the data, you can use our daily updated data with the help of api key by entering it via Altadata.

Overview

In this data product, you may find the latest and historical daily data on the COVID-19 pandemic for United States with the states level breakdown.

The COVID‑19 pandemic, also known as the coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID‑19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The outbreak was first identified in December 2019 in Wuhan, China. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March. As of 12 August 2020, more than 20.2 million cases of COVID‑19 have been reported in more than 188 countries and territories, resulting in more than 741,000 deaths; more than 12.5 million people have recovered.

The Johns Hopkins Coronavirus Resource Center is a continuously updated source of COVID-19 data and expert guidance. They aggregate and analyze the best data available on COVID-19 - including cases, as well as testing, contact tracing and vaccine efforts - to help the public, policymakers and healthcare professionals worldwide respond to the pandemic.

Methodology

• Cases and Death counts include confirmed and probable (where reported)
• Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state-level recovered cases are from COVID Tracking Project.
• Active cases = total cases - total recovered - total deaths
• Incidence Rate = cases per 100,000 persons
• Case-Fatality Ratio (%) = Number recorded deaths / Number cases
• US Testing Rate = total test results per 100,000 persons. The "total test results" are equal to "Total test results (Positive + Negative)" from COVID Tracking Project.
• US Hospitalization Rate (%) = Total number hospitalized / Number cases. The "Total number hospitalized" is the "Hospitalized – Cumulative" count from COVID Tracking Project. The "hospitalization rate" and "Total number hospitalized" are only presented for those states which provide cumulative hospital data.
• States Population data is retrieved from U.S. Census Bureau on top of the JHU CSSE's COVID-19 data

Data Source

• Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)
• U.S. Census Bureau, Population Division

Related Data Products

• COVID-19 Worldwide Daily Data

Suggested Blog Posts

• Bayesian Thinking During the Pandemic
• Impact of COVID-19 on California Electricity Demand
• Keep Calm and Look At The Fundamentals
• Markets In The Corona Virus Crisis

Data Dictionary

• Reported Date (reported_date): Covid-19 Report Date
• Province State (province_state): State name
• Population (population): Estimated state populations as of July 2019, as per U.S. Census Bureau Population Division
• Latitude (lat): Dot locations, not representative of a specific address
• Longitude (lng): Dot locations longitude, not representative of a specific address
• Confirmed Case (confirmed): Confirmed cases include presumptive positive cases and probable cases
• Active cases (active): Active cases = total confirmed - total recovered - total deaths
• Deaths (deaths): Death cases counts
• Recovered (recovered): Recovered cases counts
• Hospitalization Rate (hospitalization_rate): Total number of people hospitalized * 100...

BackgroundNepal has been devastated by an unprecedented COVID-19 outbreak, affecting people emotionally, physically, and socially, resulting in significant morbidity and mortality. Approximately 10% of COVID-19 affected people have symptoms that last more than 3–4 weeks and experience numerous symptoms causing an impact on everyday functioning, social, and cognitive function. Thus, it is vital to know about the recovered patient’s health status and undertake rigorous examinations to detect and treat infections. Hence, this study aims to assess the health status of COVID-19 post-recovery patients in Nepal.MethodA descriptive cross-sectional mixed-method study was conducted in all seven provinces of Nepal. A total of 552 interviews were conducted for the quantitative study, and 25 in-depth interviews were conducted for the qualitative study among above 18 years COVID-19-recovered patients. The data was gathered over the phone through the purposive sampling method The results of a descriptive and thematic analysis were interpreted.FindingThe majority (more than 80%) of the recovered patients could routinely perform household duties, activities outside the home, and financial job accounting. However, a few of them required assistance in carrying out all of those tasks. Prior and then after COVID-19 infection, smoking habits reduced by about one-tenth and alcohol intake decreased by a twelve percent. A qualitative finding revealed that the majority of COVID-19 symptomatic patients experienced a variety of physical symptoms such as fever, headache, body pain, fatigue, tiredness, sore throat, cough, loss of taste, loss of smell, sneezing, loss of appetite, and difficulty breathing, while others felt completely fine after being recovered. Furthermore, there was no variation in the daily functional activities of the majority of the recovered patients, while a few were found conducting fewer activities than usual because they were concerned about their health. For social health, quantitative data indicated that more than half of the participants’ social health was severely impacted. According to the IDI, the majority of the interviewees perceived society’s ignorance and misbehavior. Family members were the most often solicited sources of support. Some participants got care and assistance, but the majority did not get affection or love from their relatives. Moreover, regarding mental health, 15 percent of participants had repeated disturbing and unwanted thoughts about COVID-19 after being recovered, 16 percent tried to avoid information on COVID-19 and 7 .7 percent of people had unfavorable ideas or sentiments about themselves. More than 16 percent of participants reported feeling some level of stress related to the workplace and home. While in-depth interviews participants revealed that COVID-infected patients who were asymptomatic didn’t experience any emotional change in them but recovered patients who are symptomatic symptoms had anxiety and still being conscious of COVID-19 in fear of getting infected again Additionally, it was discovered that participants’ mental health is influenced by ignorance of society, as well as by fake news posted to social media.ConclusionCOVID-19 infection has had an impact on physical, mental, and social well-being. Hence, to aid in the early recovery of COVID-19 patients, provision of evaluating and reporting the clinical features, early detection and management of long COVID case is needed from the local and provincial and central government of Nepal.

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

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

COVID-19 Dataset for Epidemic Model Development

I combined several data sources to gain an integrated dataset involving country-level COVID-19 confirmed, recovered and fatalities cases which can be used to build some epidemic models such as SIR, SIR with mortality. Adding information regarding population which can be used for calculating incidence rate and prevalence rate. One of my applications based on this dataset is published at https://dylansp.shinyapps.io/COVID19_Visualization_Analysis_Tool/.

Content

My approach is to retrieve cumulative confirmed cases, fatalities and recovered cases since 2020-01-22 onwards from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) COVID-19 dataset, merged with country code as well as population of each country. For the purpose of building epidemic models, I calculated information regarding daily new confirmed cases, recovered cases, and fatalities, together with remaining confirmed cases which equal to cumulative confirmed cases - cumulative recovered cases - cumulative fatalities. I haven't yet to find creditable data sources regarding probable cases of various countries yet. I'll add them once I found them.

• Date: The date of the record.
• Country_Region: The name of the country/region. -alpha-3_code: country code for that can be used for map visualization.
• Population: The population of the given country/region.
• Total_Confirmed_Cases: Cumulative confirmed cases.
• Total_Fatalities: Cumulative fatalities.
• Total_Recovered_Cases: Cumulative recovered cases.
• New_Confirmed_Cases: Daily new confirmed cases.
• New_Fatalities: Daily new fatalities.
• New_Recovered_Cases: Daily new recovered cases.
• Remaining_Confirmed_Cases: Remaining infected cases which equal to (cumulative confirmed cases - cumulative recovered cases - cumulative fatalities).

Acknowledgements

1. The data source of confirmed cases, recovered cases and deaths is JHU CSSE https://github.com/CSSEGISandData/COVID-19;
2. The data source of the country-level population mainly comes from https://storage.guidotti.dev/covid19/data/ and Worldometer (https://www.worldometers.info/population/).

Inspiration

1. Building up the country-level COVID-19 case track dashboard.
2. Insights regarding the incidence rate, prevalence rate, mortality and recovery rate of various countries.
3. Building up epidemic models for forecasting.

Sociodemographic characteristics of COVID-19 recovered patients IDI participants.

An application where people can share how they recovered from COVID-19.

In the United States between February 12 and March 16, 2020, the percentage of COVID-19 patients hospitalized with the disease increased with age. Findings estimated that up to 70 percent of adults aged 85 years and older were hospitalized.

Who is at higher risk from COVID-19? The same study also found that coronavirus patients aged 85 and older were at the highest risk of death. There are other risk factors besides age that can lead to serious illness. People with pre-existing medical conditions, such as diabetes, heart disease, and lung disease, can develop more severe symptoms. In the U.S. between January and May 2020, case fatality rates among confirmed COVID-19 patients were higher for those with underlying health conditions.

How long should you self-isolate? As of August 24, 2020, more than 16 million people worldwide had recovered from COVID-19 disease, which includes patients in health care settings and those isolating at home. The criteria for discharging patients from isolation varies by country, but asymptomatic carriers of the virus can generally be released ten days after their positive case was confirmed. For patients showing signs of the illness, they must isolate for at least ten days after symptom onset and also remain in isolation for a short period after the symptoms have disappeared.

Co-existing disease of COVID-19 recovered participants.

Physical health status of COVID-19 recovered participants.

Context

Public Health England (PHE) coronavirus cases reported daily. This data shows case numbers as reported to PHE. Cases includes people who have recovered.

Content

DateVal : dd/mm/yyyy CMODateCount : The number of cases reported for the day CumCases: The cumulative number of cases IncreasePercent: The percentage increase in cases from the previous day DeathPercent: The percentage increase/decrease in daily deaths from the previous day CumCases7DayAvg: 7 day moving average of the cumulative number of cases CumDeaths7DayAvg: 7 day moving average of the cumulative number of deaths DailyDeath7DayAvg: 7 day moving average of the daily number of deaths

IncreasePercent and moving 7 day averages are calculated fields added to the original source.

Acknowledgements

https://www.gov.uk/government/publications/covid-19-track-coronavirus-cases https://coronavirus.data.gov.uk/

BackgroundNepal has been devastated by an unprecedented COVID-19 outbreak, affecting people emotionally, physically, and socially, resulting in significant morbidity and mortality. Approximately 10% of COVID-19 affected people have symptoms that last more than 3–4 weeks and experience numerous symptoms causing an impact on everyday functioning, social, and cognitive function. Thus, it is vital to know about the recovered patient’s health status and undertake rigorous examinations to detect and treat infections. Hence, this study aims to assess the health status of COVID-19 post-recovery patients in Nepal.MethodA descriptive cross-sectional mixed-method study was conducted in all seven provinces of Nepal. A total of 552 interviews were conducted for the quantitative study, and 25 in-depth interviews were conducted for the qualitative study among above 18 years COVID-19-recovered patients. The data was gathered over the phone through the purposive sampling method The results of a descriptive and thematic analysis were interpreted.FindingThe majority (more than 80%) of the recovered patients could routinely perform household duties, activities outside the home, and financial job accounting. However, a few of them required assistance in carrying out all of those tasks. Prior and then after COVID-19 infection, smoking habits reduced by about one-tenth and alcohol intake decreased by a twelve percent. A qualitative finding revealed that the majority of COVID-19 symptomatic patients experienced a variety of physical symptoms such as fever, headache, body pain, fatigue, tiredness, sore throat, cough, loss of taste, loss of smell, sneezing, loss of appetite, and difficulty breathing, while others felt completely fine after being recovered. Furthermore, there was no variation in the daily functional activities of the majority of the recovered patients, while a few were found conducting fewer activities than usual because they were concerned about their health. For social health, quantitative data indicated that more than half of the participants’ social health was severely impacted. According to the IDI, the majority of the interviewees perceived society’s ignorance and misbehavior. Family members were the most often solicited sources of support. Some participants got care and assistance, but the majority did not get affection or love from their relatives. Moreover, regarding mental health, 15 percent of participants had repeated disturbing and unwanted thoughts about COVID-19 after being recovered, 16 percent tried to avoid information on COVID-19 and 7 .7 percent of people had unfavorable ideas or sentiments about themselves. More than 16 percent of participants reported feeling some level of stress related to the workplace and home. While in-depth interviews participants revealed that COVID-infected patients who were asymptomatic didn’t experience any emotional change in them but recovered patients who are symptomatic symptoms had anxiety and still being conscious of COVID-19 in fear of getting infected again Additionally, it was discovered that participants’ mental health is influenced by ignorance of society, as well as by fake news posted to social media.ConclusionCOVID-19 infection has had an impact on physical, mental, and social well-being. Hence, to aid in the early recovery of COVID-19 patients, provision of evaluating and reporting the clinical features, early detection and management of long COVID case is needed from the local and provincial and central government of Nepal.