As of August 2, 2023, Mexico was the third Latin American country with the highest number of confirmed cases of COVID-19, reaching over 7.6 million patients. By federate entity, Mexico City ranked first in number of confirmed cases, with around 1.9 million infections recorded by September 21, 2023. The State of Mexico followed with 760,699 reported cases of the disease.

The leading cause of death in Mexico in 2020
In 2020, COVID-19 was the leading cause of death in Mexico. The country reported its first fatal case due to the disease in March 2020. Since then, the number of COVID-19 deaths has increased steadily, reaching 334,336 deaths as of August 2, 2023. These figures place Mexico fifth in the total number of deaths related to COVID worldwide and second in Latin America, just after Brazil.

Mexico’s vaccination strategy Mexico began its vaccination campaign at the end of December 2020, an immunization strategy that prioritized healthcare workers and those most at risk of developing severe COVID-19, such as the older population. With more than 223 million vaccines administered as of August 14, 2023, Mexico ranked as the Latin American country with the second highest number of applied vaccines, while slightly over three quarters of its population received at least one vaccine dose against the disease by March 2023.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

The first case of COVID-19 in Mexico was detected on March 1, 2020. By the end of the year, the total number of confirmed infections had surpassed 1.4 million. Meanwhile, the number of deaths related to the disease was nearing 148,000. On May 11, 2025, the number of cases recorded had reached 7.6 million, while the number of deaths amounted to around 335,000. The relevance of the Omicron variant Omicron, a highly contagious COVID-19 variant, was declared of concern by the World Health Organization (WHO) at the end of November 2021. As the pandemic unfolded, it became the variant with the highest share of COVID-19 cases in the world. In Latin America, countries such as Colombia, Argentina, Brazil, and Mexico were strongly affected. In fact, by 2023 nearly all analyzed sequences within these countries corresponded to an Omicron subvariant. Beyond a health crisis As the COVID-19 pandemic progressed worldwide, the respiratory disease caused by the virus SARS-CoV-2 virus first detected in Wuhan brought considerable economic consequences for countries and households. While Mexico’s gross domestic product (GDP) in current prices declined in 2020 compared to the previous year, a survey conducted among adults during the first months of 2021 showed COVID-19 impacted families mainly through finances and employment, with around one third of households in Mexico reporting an income reduction and the same proportion having at least one household member suffering from the disease.Find the most up-to-date information about the coronavirus pandemic in the world under Statista’s COVID-19 facts and figures site.

About

Contains the positive cases information up to may 2022 from Mexico. Image by the author.

"Información referente a casos COVID-19 en México " publicado por SALUD del gobierno de Mexico https://datos.gob.mx/busca/dataset/informacion-referente-a-casos-covid-19-en-mexico 01/05/2022

Mexico SALUD: COVID-19: Confirmed Cases: To Date: Jalisco data was reported at 277,335.000 Person in 17 Aug 2022. This records an increase from the previous number of 276,948.000 Person for 16 Aug 2022. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Jalisco data is updated daily, averaging 86,289.000 Person from Feb 2020 (Median) to 17 Aug 2022, with 902 observations. The data reached an all-time high of 277,335.000 Person in 17 Aug 2022 and a record low of 0.000 Person in 13 Mar 2020. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Jalisco data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table MX.D001: Ministry of Health: Coronavirus Disease 2019 (COVID-2019) (Discontinued). Current day data is released daily between 7PM and 11PM Mexico City Time. Weekend data are updated following Monday morning, Hong Kong Time. Number of Confirmed Cases are based on the state where it is reported.

Mexico COVID-19 clinical data 🦠🇲🇽

This dataset contains the results of real-time PCR testing for COVID-19 in Mexico as reported by the [General Directorate of Epidemiology](https://www.gob.mx/salud/documentos/datos-abiertos-152127).

The official, raw dataset is available in the Official Secretary of Epidemiology website: https://www.gob.mx/salud/documentos/datos-abiertos-152127.

You might also want to download the official column descriptors and the variable definitions - e.g. SEXO=1 -> Female; SEXO=2 -> Male; SEXO=99 -> Undisclosed) - in the following [zip file](http://datosabiertos.salud.gob.mx/gobmx/salud/datos_abiertos/diccionario_datos_covid19.zip). I've maintained the original levels as described in the official dataset, unless otherwise specified.

IMPORTANT: This dataset has been maintained since the original data releases, which weren't tabular, but rather consisted of PDF files, often with many/different inconsistencies which had to be resolved carefully and is annotated in the .R script. More later datasets should be more reliable, but earlier there were a lot of things to figure out like e.g. when the official methodology to assign the region of the case was changed to be based on residence rather than origin). I've added more notes on very early data here: https://github.com/marianarf/covid19_mexico_data.

Context

The data obtained from the Mexico's General Direction of Epidemiology contains multiple information on the current pandemic situation. However, these data are saturated with features that may not be very useful in a predictive analysis.

Due to this I decided to clean and format the original data and generate a dataset that groups confirmed, dead, recovered and active cases by State, Municipality and Date.

This is very useful if you want to generate geographically specific models

Content

The data set contains the covid cases columns (positive, dead, recovered and active) that are counted by state and municipality.

I.e

Would you like to see the data cleaning notebook? You can check it in my Github

Classification criteria

• Recovered cases: If the patient is not dead and it has been more than 15 days then he is considered as recovered.
• Active cases: If the patien isn't recovered an isn't dead then is active

Time lapse

The first documented case is on 2020-01-13. The dataset will be updated every day adding new cases

Acknowledgements

For this project, the data are obtained from the official URL of the government of México whose author is “Dirección General de Epidemiología”:

Corona Virus Data: https://www.gob.mx/salud/documentos/datos-abiertos-152127

Data Dictionary: https://www.gob.mx/salud/documentos/datos-abiertos-152127

Differences in results

According to the official results obtained from: https://coronavirus.gob.mx/datos/

• The main difference between the official data and this dataset is in the recovered cases. This is because the Mexican government only considers outpatient cases when counting recovered cases. This dataset considers outpatient and inpatient cases when counting recovered people.

• The second difference is some rows that contained nonsense information(I think this was a data collection error by the institution), these were eliminated.

Brazil is the Latin American country affected the most by the COVID-19 pandemic. As of May 2025, the country had reported around 38 million cases. It was followed by Argentina, with approximately ten million confirmed cases of COVID-19. In total, the region had registered more than 83 million diagnosed patients, as well as a growing number of fatal COVID-19 cases. The research marathon Normally, the development of vaccines takes years of research and testing until options are available to the general public. However, with an alarming and threatening situation as that of the COVID-19 pandemic, scientists quickly got on board in a vaccine marathon to develop a safe and effective way to prevent and control the spread of the virus in record time. Over two years after the first cases were reported, the world had around 1,521 drugs and vaccines targeting the COVID-19 disease. As of June 2022, a total of 39 candidates were already launched and countries all over the world had started negotiations and acquisition of the vaccine, along with immunization campaigns. COVID vaccination rates in Latin America As immunization against the spread of the disease continues to progress, regional disparities in vaccination coverage persist. While Brazil, Argentina, and Mexico were among the Latin American nations with the most COVID-19 cases, those that administered the highest number of COVID-19 doses per 100 population are Cuba, Chile, and Peru. Leading the vaccination coverage in the region is the Caribbean nation, with more than 406 COVID-19 vaccines administered per every 100 inhabitants as of January 5, 2024.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In past 24 hours, Mexico, North America had N/A new cases, N/A deaths and N/A recoveries.

For the historic files from 12 April 2020 check my repo: Covid-19 Mexico public information

Context

Official posted data from the Mexican Health Department.

Content

Confirmed cases -> casos_confirmados

Suspicious cases -> casos_sospechosos

Complete information -> covid-19_general_MX

Acknowledgements

Secretaría de Salud - Mexican Gobernment: covid-19_general latest published information

historic covid-19_general

Independent suspicious and confirmed cases files stopped being distributed by the government on April 18th 2020 I'll add them again in case they publish them.

Mexico recorded 7603871 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Mexico reported 334013 Coronavirus Deaths. This dataset includes a chart with historical data for Mexico Coronavirus Cases.

Mexico SALUD: COVID-19: Confirmed Cases: New data was reported at 0.000 Person in 24 Oct 2022. This stayed constant from the previous number of 0.000 Person for 23 Oct 2022. Mexico SALUD: COVID-19: Confirmed Cases: New data is updated daily, averaging 4,793.500 Person from Feb 2020 (Median) to 24 Oct 2022, with 970 observations. The data reached an all-time high of 60,552.000 Person in 19 Jan 2022 and a record low of 0.000 Person in 24 Oct 2022. Mexico SALUD: COVID-19: Confirmed Cases: New data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table MX.D001: Ministry of Health: Coronavirus Disease 2019 (COVID-2019) (Discontinued). Current day data is released daily between 7PM and 11PM Mexico City Time. Weekend data are updated following Monday morning, Hong Kong Time. As of Oct 07, cases confirmed by clinical-epidemiological association to COVID-19 are included on the count of Confirmed Cases and Deaths. These cases are suspected cases or those who has symptoms but were unable to have a test or received medical attention before dying.

Mexico SALUD: COVID-19: Confirmed Cases: To Date: Oaxaca data was reported at 144,158.000 Person in 17 Aug 2022. This records an increase from the previous number of 143,948.000 Person for 16 Aug 2022. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Oaxaca data is updated daily, averaging 46,424.000 Person from Feb 2020 (Median) to 17 Aug 2022, with 902 observations. The data reached an all-time high of 144,158.000 Person in 17 Aug 2022 and a record low of 0.000 Person in 13 Mar 2020. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Oaxaca data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table MX.D001: Ministry of Health: Coronavirus Disease 2019 (COVID-2019) (Discontinued). Current day data is released daily between 7PM and 11PM Mexico City Time. Weekend data are updated following Monday morning, Hong Kong Time. Number of Confirmed Cases are based on the state where it is reported.

Context

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. During the entire course of the pandemic, one of the main problems that healthcare providers have faced is the shortage of medical resources and a proper plan to efficiently distribute them. In these tough times, being able to predict what kind of resource an individual might require at the time of being tested positive or even before that will be of immense help to the authorities as they would be able to procure and arrange for the resources necessary to save the life of that patient.

The main goal of this project is to build a machine learning model that, given a Covid-19 patient's current symptom, status, and medical history, will predict whether the patient is in high risk or not.

content

The dataset was provided by the Mexican government (link). This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.

• sex: 1 for female and 2 for male.
• age: of the patient.
• classification: covid test findings. Values 1-3 mean that the patient was diagnosed with covid in different degrees. 4 or higher means that the patient is not a carrier of covid or that the test is inconclusive.
• patient type: type of care the patient received in the unit. 1 for returned home and 2 for hospitalization.
• pneumonia: whether the patient already have air sacs inflammation or not.
• pregnancy: whether the patient is pregnant or not.
• diabetes: whether the patient has diabetes or not.
• copd: Indicates whether the patient has Chronic obstructive pulmonary disease or not.
• asthma: whether the patient has asthma or not.
• inmsupr: whether the patient is immunosuppressed or not.
• hypertension: whether the patient has hypertension or not.
• cardiovascular: whether the patient has heart or blood vessels related disease.
• renal chronic: whether the patient has chronic renal disease or not.
• other disease: whether the patient has other disease or not.
• obesity: whether the patient is obese or not.
• tobacco: whether the patient is a tobacco user.
• usmr: Indicates whether the patient treated medical units of the first, second or third level.
• medical unit: type of institution of the National Health System that provided the care.
• intubed: whether the patient was connected to the ventilator.
• icu: Indicates whether the patient had been admitted to an Intensive Care Unit.
• date died: If the patient died indicate the date of death, and 9999-99-99 otherwise.

Covid 19 cases in the american continent.

Sources

Mexico "Información referente a casos COVID-19 en México " publicado por SALUD del gobierno de Mexico https://datos.gob.mx/busca/dataset/informacion-referente-a-casos-covid-19-en-mexico 01/05/2022

Brazil https://www.kaggle.com/datasets/unanimad/corona-virus-brazil

USA https://www.kaggle.com/datasets/headsortails/covid19-us-county-jhu-data-demographics

Argentina http://datos.salud.gob.ar/dataset/covid-19-casos-registrados-en-la-republica-argentina Licencia Creative Commons Attribution 4.0

Chile https://github.com/MinCiencia/Datos-COVID19/tree/master/output/producto3

Peru https://www.datosabiertos.gob.pe/dataset/casos-positivos-por-covid-19-ministerio-de-salud-minsa Open Data Commons Attribution License

Colombia https://www.datos.gov.co/Salud-y-Protecci-n-Social/Casos-positivos-de-COVID-19-en-Colombia/gt2j-8ykr/data

Canada https://github.com/ccodwg/CovidTimelineCanada

Content

COVID-19 data for Mexico, consist of two main datasets: time_series_confirmed_MX: time series of confirmed cases by state. time_series_deaths_MX: time series of deaths by state The data will be updated every day at the start of Secretaría de Salud conference (18:00), with last information recived at 13:00.
If you want the data in github form: https://github.com/carloscerlira/COVIDMX.

Source

https://www.gob.mx/salud/archivo/documentos?idiom=es&filter_id=395&filter_origin=archive

Mexico SALUD: COVID-19: Confirmed Cases: To Date: Queretaro data was reported at 175,142.000 Person in 17 Aug 2022. This records an increase from the previous number of 174,943.000 Person for 16 Aug 2022. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Queretaro data is updated daily, averaging 69,521.500 Person from Feb 2020 (Median) to 17 Aug 2022, with 902 observations. The data reached an all-time high of 175,142.000 Person in 17 Aug 2022 and a record low of 0.000 Person in 10 Mar 2020. Mexico SALUD: COVID-19: Confirmed Cases: To Date: Queretaro data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table MX.D001: Ministry of Health: Coronavirus Disease 2019 (COVID-2019) (Discontinued). Current day data is released daily between 7PM and 11PM Mexico City Time. Weekend data are updated following Monday morning, Hong Kong Time. Number of Confirmed Cases are based on the state where it is reported.

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.

Context

Currently the Dirección General de Epidemiología publishes a daily report of people who might be positive case of COVID-19, unfortunately the format is in pdf

I wanted to make this information easy to consume for data analysis and visualization.

Content

This data set is the daily report about people who might be a positive case of COVID-19, the same data from Coronavirus (COVID-19) -Comunicado Técnico Diario but in .csv format

https://www.gob.mx/salud/documentos/nuevo-coronavirus-2019-ncov-comunicado-tecnico-diario

Acknowledgements

Many thanks to Dirección General de Epidemiología for publishing the daily reports

This Project Tycho dataset includes a CSV file with COVID-19 data reported in MEXICO: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

According to a survey carried out in July 2020, ** percent of respondents in Mexico said they did not know any family member, friend, neighbor or co-worker who had contracted COVID-19, while ** percent stated knowing one or two people that had fallen ill with with this strain of coronavirus.