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Pakistan recorded 1580631 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Pakistan reported 30656 Coronavirus Deaths. This dataset includes a chart with historical data for Pakistan Coronavirus Cases.

Pakistan COVID-19 Dataset

This is the data repository for the 2019 Novel Coronavirus cases in Pakistan.

Daily reports (daily_reports)

This folder contains daily case reports. All timestamps are in UTC (GMT+0). Provincial Data is only available from 11th April 2020, previous reports have data of Pakistan as whole.

File naming convention

YYYY-MM-DD.csv in UTC.

Field description

• Province_State: Province, state or dependency name.
• Country_Region: Country, region or sovereignty name.
• Last Update: YYYY-MM-DD HH:mm:ss (24 hour format, in UTC).
• Lat and Long_: Latitude and Longitude locations on the map. All points shown on the map are based on geographic centroids, and are not representative of a specific address, building or any location at a spatial scale finer than a province/state.
• Confirmed: Counts include confirmed and probable (where reported).
• Deaths: Counts include confirmed and probable (where reported).
• Recovered: 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.
• Active: Active cases = total cases - total recovered - total deaths.
• Incident_Rate: Incidence Rate = cases per 100,000 persons.
• Case_Fatality_Ratio (%): Case-Fatality Ratio (%) = Number recorded deaths / Number cases.
• All cases, deaths, and recoveries reported are based on the date of initial report.

Combined report (combined_report.csv)

This file contains all the daily cases reports combined into one.

Data sources

• Government of Pakistan
• JHU CSSE COVID-19 Dataset

Context: The 2019–20 coronavirus pandemic was confirmed to have reached Pakistan on 26 February 2020, when a student in Karachi tested positive upon returning from Iran. By 18 March, cases had been registered in all four provinces, the two autonomous territories, and the federal territory of Islamabad. The dataset is completely acquired from NIH Publications, Governmental resources and extra mile contacts. The dataset reflects at provincial level and details from all the aspects. Complete details can be visualized at hyperurl.co/pakcovid Content: The dataset contains chronological seven tabs and 80+ columns with data ranging from Suspected Cases Last Date Suspected Cases Last 24 Hrs Suspected Cases Cumulative Lab Tests Last 24 Hrs Lab Tests Cumulative Confirmed Cases Last Date Confirmed Cases Last 24 Hrs Confirmed Cases Cumulative Deaths Last Date Deaths Last 24 Hrs Deaths Cumulative Transmission Total Transmission Foreign - Iran Transmission Foreign - Iran % Transmission Foreign - Other Transmission Foreign - Other % Transmission Local - Tableegh Transmission Local % - Tableegh Transmission Local - Others Transmission Local % - Others Transmission Local Transmission Local % Total Hospitals Beds for COVID Total Admitted Admitted Stable Admitted Critical Admitted Ventilator Home Quarantine Recovered Death Quarantine Facilities Last 24 Hrs Arrival Last 24 Hrs (Location) Last 24 Hrs Departure Cumulative Quarantined Number of Tests Results Achieved Test Positive Cases Test Positive Cases % Confirmed HW - Active Doctors Confirmed HW - Active Nurses Confirmed HW - Active Others Confirmed HW - Active Total Confirmed HW - Active Isolation Confirmed HW - Active Hospital Confirmed HW - Active Hospital Stable Confirmed HW - Active Hospital Ventilator Confirmed HW - Active Recovered Confirmed HW - Active Deaths all at provincial level The first version has the data from first case of February 26 2020 to April 19, 2020. We intend to publish weekly updates Data Source: National Institute of Health website Daily publication Processed via Python Camelot Package. Visit https://github.com/MesumRaza for details on scripting. Acknowledgements: Users are allowed to use, copy, distribute and cite the dataset as follows: “Mesum Raza Hemani, Corona Virus Pakistan Dataset 2020, Kaggle Dataset Repository”

In past 24 hours, Pakistan, Asia had N/A new cases, N/A deaths and N/A recoveries.

Context

With COVID-19 spread world-wide, it is essential to have a clear understanding of its spread.

Content

The data has date-wise cases for each province/region of Pakistan.

Acknowledgements

The data is compiled from Pakistan govt website http://covid.gov.pk/

Inspiration

I would like to see how much the spread will grow in coming days and would it become as bad as other nations in the world?

New deaths from Covid during a month in Pakistan, March, 2023 The most recent value is 6 new deaths from Covid as of March 2023, an increase compared to the previous value of 3 new deaths from Covid. Historically, the average for Pakistan from February 2020 to March 2023 is 807 new deaths from Covid. The minimum of 0 new deaths from Covid was recorded in February 2020, while the maximum of 3324 new deaths from Covid was reached in April 2021. | TheGlobalEconomy.com

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

Discover the latest resources, maps and information about the coronavirus (COVID-19) outbreak in your community

Using a sample of 1,211 households in Pakistan, we examine the effects of COVID-19 on three key domains: education, economic, and health-related. First, during school closures, 66 percent of surveyed households report not using technology for learning at all. Wealth disparities mar access to distance learning, and richer households are 39 percent more likely to use technology for learning compared to the poorest households. This has implications for learning remediation as children head back to school. Second, more than half of the respondents report a reduction in income and one-fifth report being food insecure during the lockdown in the first week of May, 2020. Only one-fifth of households reporting a reduction in income and one-fifth of respondents reporting a reduction in the number of meals consumed report being covered by the federal government’s cash transfer program. Third, while a majority of respondents (90 percent) report adopting precautionary measures such as face masks, a vast majority of respondents (78 percent) underestimate the risk of contracting a COVID-19 infection compared to tuberculosis. With schools reopening in a phased manner since mid-September, most respondents (68 percent) believe that school reopenings will further increase the risk of COVID-19 infections. (2020)

Analysis of ‘Pakistan Corona Virus Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/zusmani/pakistan-corona-virus-citywise-data on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

Pakistan witnessed its first Corona virus patient on February 26th 2020. It's a bumpy ride since then. The cases are increasing gradually and we haven't seen the worst yet. While, there are few government resources for cumulative updates, there is no place where you can find the city level patients data. It's also not possible to find the running chronological tally of patients as they test positive. We have decided to create our own dataset for all the researchers out there with such details so we can model the infection spread and forecast the situation in coming days. We hope, by doing so, we will be able to inform policy makers on various intervention models, and healthcare professionals to be ready for the influx of new patients. We certainly hope, that this little contribution will go a long way for saving lives in Pakistan

Content

The dataset contains seven columns for date, number of cases, number of deaths, number of people recovered, travel history of those cases, and location of the cases (province and city).

The first version has the data from first case of February 26 2020 to April 19, 2020. We intend to publish weekly updates

Acknowledgements

Users are allowed to use, copy, distribute and cite the dataset as follows: “Zeeshan-ul-hassan Usmani, Sana Rasheed, Pakistan Corona Virus Data, Kaggle Dataset Repository, April 19, 2020.”

Inspiration

Some ideas worth exploring:

Can we find the spread factor for the Corona virus in Pakistan?

How long it takes for a positive case to infect another in Pakistan?

How we can use this data to simulate lock down scenarios and find its impact on country's economy? Here is a good
read to get started - http://zeeshanusmani.com/urdu/corona-economic-impact/

How does Pakistan Corona virus spread compare against its neighbors and other developed counties?

What would be the impact of this infection spread on country's economy and people living under poverty? Here are two briefs to get you started

http://zeeshanusmani.com/urdu/corona/ http://zeeshanusmani.com/urdu/corona-what-to-learn/

How do we visualize this dataset to inform policy makers? Here is one example https://zeeshanusmani.com/corona/

Can we predict the number of cases in next 10 days and a month?

--- Original source retains full ownership of the source dataset ---

This dataset demonstrates the fear of Coronavirus (COVID-19) among the people of Khyber Pakhtunkhwa (Pakistan), their preventive behaviour, mental health condition, and level of anxiety during the pandemic. To gauge these constructs, a questionnaire was developed with the help of various scales – Fear of COVID-19 Scale (FCV-19S), Positive Mental Health Scale (PMHS), and General Anxiety Disorder Scale (GAD). At the time of data collection, the COVID-19 cases were emerging rapidly in the country due to which the KPK province was also facing lock-down and other mobility restrictions to limit the spread of viral infection. Keeping in view the prevalent emergency conditions, the research tool was developed in Google form and disseminated online for the collection of data. The informed consent of the respondents was obtained electronically, and they participated voluntarily in this survey research. Social media apps like Facebook, WhatsApp, LinkedIn, and personal contacts were also used for speedy collection of data. All the questions in the questionnaire were mandatory and the respondents could not send their responses by skipping any of them, so there is no missing value in the dataset. A total of 501 responses were received out of which 208 were females. For the convenience of the participants, every question in the questionnaire was translated into the Urdu language. All the responses were automatically saved online into a .xlsx spreadsheet and later that data was converted to digitized form by developing a coding frame. There are two main sections in this dataset, first is about the socio-demographic information (gender, age, marital status, employment status, area of residence and education) of the participants and the second demonstrates the fear, mental health, preventive behaviour, and anxiety while in the second section, the responses were rated on Likert scale. This dataset could be beneficial to the researchers and policymakers as they can get further insight to develop better skills and practices from a rapidly evolving situation.

Context

The 2019–20 coronavirus pandemic was confirmed to have reached Pakistan on 26 February 2020, when a student in Karachi tested positive upon returning from Iran. By 18 March, cases had been registered in all four provinces, the two autonomous territories, and the federal territory of Islamabad. The dataset is completely acquired from NIH Publications, Governmental resources and extra mile contacts.

The dataset reflects at provincial level and details from all the aspects. Complete details can be visualized at hyperurl.co/pakcovid

Content

The dataset contains chronological seven tabs and 80+ columns with data ranging from Suspected Cases Last Date Suspected Cases Last 24 Hrs Suspected Cases Cumulative Lab Tests Last 24 Hrs Lab Tests Cumulative Confirmed Cases Last Date Confirmed Cases Last 24 Hrs Confirmed Cases Cumulative Deaths Last Date Deaths Last 24 Hrs Deaths Cumulative Transmission Total Transmission Foreign - Iran Transmission Foreign - Iran % Transmission Foreign - Other Transmission Foreign - Other % Transmission Local - Tableegh Transmission Local % - Tableegh Transmission Local - Others Transmission Local % - Others Transmission Local Transmission Local % Total Hospitals Beds for COVID Total Admitted Admitted Stable Admitted Critical Admitted Ventilator Home Quarantine Recovered Death Quarantine Facilities Last 24 Hrs Arrival Last 24 Hrs (Location) Last 24 Hrs Departure Cumulative Quarantined Number of Tests Results Achieved Test Positive Cases Test Positive Cases % Confirmed HW - Active Doctors Confirmed HW - Active Nurses Confirmed HW - Active Others Confirmed HW - Active Total Confirmed HW - Active Isolation Confirmed HW - Active Hospital Confirmed HW - Active Hospital Stable Confirmed HW - Active Hospital Ventilator Confirmed HW - Active Recovered Confirmed HW - Active Deaths all at provincial level

The first version has the data from first case of February 26 2020 to April 19, 2020. We intend to publish weekly updates

Acknowledgements

Users are allowed to use, copy, distribute and cite the dataset as follows: “Mesum Raza Hemani, Corona Virus Pakistan Dataset 2020, Kaggle Dataset Repository”

Visualization

Interactive Link: Desktop Mobile

The number of COVID-19 vaccination doses administered per 100 people in Pakistan rose to 144 as of Oct 27 2023. This dataset includes a chart with historical data for Pakistan Coronavirus Vaccination Rate.

Dataset

This dataset was created by AqibRehman PirZada

Contents

Background: Outbreak of COVID-19, in many countries, has imposed a lockdown on their residents. The usefulness of extenuative actions is extremely reliant on society's knowledge, attitudes, and practices (KAP) toward pandemic control.Objective: This study aimed to explore the awareness, attitudes, and practices of the general Pakistani population to COVID-19.Methods: From June 13, 2020, until June 30, 2020, a cross-sectional online KAP survey was conducted among the Pakistani public. For data collection, a validated self-administered questionnaire was used. The survey instrument consisted of six demographic characteristics, 14 items on knowledge, four on attitudes, and six items on practices, modified from a previously published questionnaire on COVID-19.Results: The present study included 2,307 participants, 58.3% males and 41.7% of females. The majority (86.7%) sought information from social media (SM) and television, 95% had good practices, 89.9% had positive attitudes, and two-thirds (67.4%) of the respondents had adequate knowledge. The students and people from younger age groups had more positive attitudes compared with others. Highly educated w with other groups (p < 0.001). In logistic regression analysis, the odds ratio indicated that the private job was negatively associated, and high monthly income was positively associated with adequate knowledge (OR = 0.595). Old age was the predictor of negative attitude, and high school degrees and master's degrees were associated with good practice scores.Conclusion: The Pakistani general population has an overall positive attitude and proactive practices against COVID-19, but their knowledge is inadequate. The most important source of information was SM, followed by television. These are playing a crucial role in educating the Pakistani public.

WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Pakistan data was reported at 1,580,631.000 Person in 24 Dec 2023. This stayed constant from the previous number of 1,580,631.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Pakistan data is updated daily, averaging 1,371,202.500 Person from Feb 2020 (Median) to 24 Dec 2023, with 1398 observations. The data reached an all-time high of 1,580,631.000 Person in 24 Dec 2023 and a record low of 0.000 Person in 27 Feb 2020. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Pakistan data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

Background and Objectives: In order to curb the spread of coronavirus disease 2019 (COVID-19), the countries took preventive measures such as lockdown and restrictions of movements. This can lead to effects on mental health of the population. We studied the impact of COVID-19 on psychological well-being and associated factors among the Pakistani general population.Methods: An online cross-sectional survey was conducted between 26th April and 15th May and included participants from all over the Pakistan. Attitudes and worriedness about COVID-19 pandemic were assessed using a structured questionnaire. A validated English and Urdu version of the World Health Organization Well-Being Index (WHO-5) was used to assess the well-being. Factor analysis was done to extract the attitude item domains. Logistic regression was used to assess the factors associated with poor well-being.Results: A total of 1,756 people participated in the survey. Almost half 50% of the participants were male, and a similar proportion was employed. About 41% of the participants were dependent on financial sources other than salary. News was considered a source of fear as 72% assumed that avoiding such news may reduce the fear. About 68% of the population was worried about contracting the disease. The most common coping strategies used during lockdown were spending quality time with family, eating healthy food, adequate sleep, and talking to friends on phone. Prevalence of poor well-being was found to be 41.2%. Female gender, being unemployed, living in Sindh and Islamabad Capital Territory (ICT), fear of COVID-19, and having chronic illness were significantly associated with poor well-being. Similarly, coping strategies during lockdown (doing exercise; spending time with family; eating healthy food; having good sleep; contributing in social welfare work and spending time on hobbies) were also significantly associated with mental well-being.Conclusion: We found a high prevalence 41.2% of poor well-being among the Pakistani general population. We also investigated risk factors of poor well-being which included female gender, unemployment, being resident of ICT and Sindh, fear, chronic illness, and absence of coping strategies. This calls for immediate action at population level in the form of targeted mass psychological support programs to improve the mental health of population during the COVID-19 crises.

Whereas most of the evidence generated from the start of the global pandemic, COVID-19, focuses on epidemiological, diagnostic and clinical aspects of the illness, importance of social aspects has also been highlighted. This has been included as one of the 34 knowledge gaps specified in the WHO R&D Blueprint WHO 2019 Novel Coronavirus Global research and innovation forum: towards a research roadmap published recently. One of the key approaches to containing COVID-19 has been self-quarantine and social distancing, which although is the need of the day but not easy to manage posing multiple challenges especially in a Pakistani community which follows strong cultural and social beliefs. It is, therefore important to identify the perception, practice and attitude of the community towards containing this disease. These insights are important for national health officials planning to implement control measures in an existing diverse socio-cultural system, an aspect which has been highlighted in the National Action Plan (NAP) for COVID-19 in Pakistan, published on 13th March 2020.

For further information, see: https://www.ed.ac.uk/usher/respire/covid-19/community-perception-public-health-measures

The COVID-19 pandemic is striking the world with serious public health and socioeconomic complications. The pandemic has influenced all forms of daily life, including educational institutions. Therefore, this cross-sectional survey was conducted to understand knowledge, attitudes, and practices related to COVID-19 among the students of the University of Veterinary and Animal Sciences, Lahore. The data was collected using an online self-directed questionnaire. The survey form includes six items about sociodemographic characteristics, 14 knowledge-based questions, seven questions on attitude, and eight questions on practices. The sample number was calculated using the Raosoft sample size calculator. A total number of 3,854 students, including 1,823 men and 2,031 women, were engaged in this survey, having student representation from all the provinces in the country. The data were analyzed using a chi-square test. A total of 97% of the students knew that the etiological agent of COVID-19 is a virus and that it is a disease of the respiratory system (94%). Many students kept visiting their relatives during the lockdown (45%), and their relatives kept visiting them at home (59%). The responses from the students varied a lot on specific questions about the transmission of the virus. Women tended to have less information regarding precautionary travel measures (p < 0.01), but supplemental knowledge of prevention of disease transmission from positive patients (p < 0.01). Conclusively, the majority of the university students surveyed had imperative knowledge, a good attitude, and active practice in response to the COVID-19 outbreak. Moreover, the KAP scores have varied by demography, gender, and the number of family members. Therefore, continuous awareness of preventative behaviors should be disseminated regularly in emergencies.