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

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

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

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.

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)

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.

Covid vaccinated people per hundred people in Pakistan, March, 2023 The most recent value is 69.07 Covid vaccinated people per hundred people as of March 2023, an increase compared to the previous value of 68.79 Covid vaccinated people per hundred people. Historically, the average for Pakistan from February 2021 to March 2023 is 40.75 Covid vaccinated people per hundred people. The minimum of 0.03 Covid vaccinated people per hundred people was recorded in February 2021, while the maximum of 69.07 Covid vaccinated people per hundred people was reached in March 2023. | TheGlobalEconomy.com

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.

This Project Tycho dataset includes a CSV file with COVID-19 data reported in PAKISTAN: 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", "Pakistan Ministry of Health COVID-19 Dashboard", "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.

Pakistan recorded 903484 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, Pakistan reported 28839 Coronavirus Deaths. This dataset includes a chart with historical data for Pakistan Coronavirus Recovered.

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.

Goodness of fit measures for Covid-19 data of Pakistan.

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).

View daily updates and historical trends for Pakistan Coronavirus Full Vaccination Rate. Source: Our World in Data. Track economic data with YCharts analy…

COVID-19 Pakistani Patients X-ray Image Dataset

A team of researchers from Edinburgh Napier University UK, HITEC University Taxila, and PNEC Karachi, Pakistan along with their collaborators from Kingdom of Saudi Arabia and in collaboration with medical doctors have created a database of chest X-ray images for COVID-19 positive and Normal images. This dataset has 390 COVID-19 and 60 Normal Images.

Please cite following article if you use this dataset:

Umair, M.; Khan, M.S.; Ahmed, F.; Baothman, F.; Alqahtani, F.; Alian, M.; Ahmad, J. Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset. Sensors 2021, 21, 5813. https://doi.org/10.3390/s21175813

Link to article: https://www.mdpi.com/1424-8220/21/17/5813

Dataset

This dataset was created by iTz HasEeb

Contents

Dataset

This dataset was created by AqibRehman PirZada

Contents

Total Covid cases per million people in Pakistan, March, 2023 The most recent value is 6698 cases per million as of March 2023, an increase compared to the previous value of 6687 cases per million. Historically, the average for Pakistan from February 2020 to March 2023 is 4166 cases per million. The minimum of 0 cases per million was recorded in February 2020, while the maximum of 6698 cases per million was reached in March 2023. | TheGlobalEconomy.com

Distribution of observed and simulated daily new cases, daily deaths, and daily recover cases of COVID-19 in Pakistan.

COVID-19 is a pandemic having devastating implications on healthcare systems globally. Evidence shows that COVID-19 infected patients with pneumonia may present on chest x-rays with a pattern that is difficult to characterise using only the human eye. Therefore, artificial intelligence (AI) techniques using deep learning, which can consistently identify infected patients from non-infected ones given a radiographic examination of the patient, can be used as a reliable diagnostic tool. Considering chest x-rays are one of the most commonly performed radiological studies (coupled with the near universal availability of testing machines), applying AI techniques on them could prove to be valuable for COVID-19 diagnosis during clinical management. We therefore aim to establish a reliable diagnostic tool based on a deep-learning framework for the screening of patients who present with COVID-19 related abnormalities on chest x-rays. Over the course of 7 months we will build a dataset using open source data which are freely available, as well as with de-identified patient data collected from health institutions in Pakistan. Using this dataset, a deep learning model will be trained, which would be able to accurately screen patients who present with abnormalities relevant to COVID-19 in their radiographic examination. This tool will ultimately aid in expediting the diagnosis and referral of COVID-19 patients, resulting in improved clinical outcomes.

For further information, see: https://www.ed.ac.uk/usher/respire/covid-19/covid-19-detection-chest-x-rays