ArticlePublic health2021
Identification of potential lockdown areas during COVID-19 transmission in Punjab, Pakistan.
Article in Public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Antifungal Resistance Among Candida Species: Diagnostic and Clinical Challenges in Specialized Cancer Care Hospital of Lahore.Journal of clinical laboratory analysis · 2025Article
- Knowledge, Attitude, And Practices Regarding COVID-19 (Coronavirus) Infection Control and Prevention among Radiology Staff; a Perspective from Largest Private Tertiary Care Hospital in Pakistan.Archives of Razi Institute · 2025Article
- Lifestyle and Dietary Habits Change Before and During Quarantine and Subsequent Weight Gain.Journal of community hospital internal medicine perspectives · 2023Article
- National IoMT platform strategy portfolio decision model under the COVID-19 environment: based on the financial and non-financial value view.Annals of operations research · 2022Article
- A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020.Transactions in GIS : TG · 2021Review
- SARS-CoV-2 (Covid-19) vaccines structure, mechanisms and effectiveness: A review.International journal of biological macromolecules · 2021Review
- A Cross-Sectional Survey of Pakistani Muslims Coping with Health Anxiety through Religiosity during the COVID-19 Pandemic.Journal of religion and health · 2021Article
- An Overview of the Treatment Options Used for the Management of COVID-19 in Pakistan: Retrospective Observational Study.JMIR public health and surveillance · 2021Observational
- Prevalence and Associated Risk Factor of COVID-19 and Impacts of Meteorological and Social Variables on Its Propagation in Punjab, Pakistan.Earth systems and environment · 2021Article
- "Underneath the visible" - COVID-19 Risk prediction tools in a high-volume, low-resource Emergency Department.Pakistan journal of medical sciencesArticle
- Urban COVID-19 endemism in Petrópolis: detection of an endemic focus by spatial analysis.Revista peruana de medicina experimental y salud publicaArticle
- Epidemiological and Clinical Characteristics of COVID-19: A Retrospective Multi-Center Study in Pakistan.Frontiers in public healthArticle
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesReal-time COVID-19 spread mapping and monitoring to identify lockdown and semi-lockdown areas using hotspot analysis and geographic information systems and also near future prediction modeling for risk of COVID-19 in Punjab, Pakistan. STUDY
designData for all COVID-19 cases were collected until 20 October 2020 in Punjab Province.
methodsThe methodology included geotagging COVID-19 cases to understand the trans-mobility areas for COVID-19 and characterize risk. The hotspot analysis technique was used to identify the number of areas in danger zones and the number of people affected by COVID-19. The complete lockdown areas were marked down geographically to be selected by the government of Pakistan based on increased numbers of cases.
resultsAs per predictive model estimates, almost 9.2 million people are COVID-19 infected by 20 October 2020 in Punjab Province. The compound growth rate of COVID-19 decreased to 0.012% per day and doubling rate increased to 364.5 days in Punjab Province. Based on Pueyo model predictions from past temporal data, it is more likely that Punjab and Pakistan entered into peak around the first week of July 2020, and the decline of growth rate (and doubling rate) of reported cases started afterward. Hospital load was also measured through the Pueyo model, and mostly, people in the 60+ years age group are expected to dominate the hospitalized population.
conclusionsPakistan is experiencing a high number of COVID-19 cases, with the maximum share from Punjab, Pakistan. Statistical modeling and compound growth estimation formulation were done through the Pueyo model, which was applied in Pakistan to identify the compound growth of COVID-19 patients and predicting numbers of patients shortly by slightly modifying it as per the local context.
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