Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective: To determine the prevalence of COVID-19 during the second wave in Chitral, Pakistan.Study Design: Cross sectional prevalence study.Place and Duration of the Study: The study was conducted in Health Department of Agha Khan Health Servicest th (AKHS) Chitral from 1 September 2020 to 31 March 2021.Material and Methods: This data has been collected from Agha Khan Health Service (AKHS) of Chitral duringthe second wave. The positive cases reported were tested using PCR. A prevalence-based study was conductedto analyze the severity of COVID-19 in Chitral during second wave. A total of 2315 suspected symptomaticindividuals consented for whole blood samples and nasal swabs for viral antigen detection by PCR. RNAextraction was performed using EMAG (BIOMERIUX, France). Real-time reverse-transcription PCR wasperformed to detect the viral load.Results: The second wave of COVID-19 in Chitral district did not cause any serious harm because of thevaccination and public awareness about the infection and social distancing. Overall, 15% of the population wastested positive and the peak was in months of November and December 2020. The higher rate of positivity(69%) was shown in upper rural areas of Chitral district, KP province, Pakistan More than 70% of population gotvaccinated by March 2021 that is the highest number of vaccinated people in a city in Pakistan.Conclusion: Our prevalence based data analysis indicate that the second wave of Corona virus hit the countrybut had limited effects in Chitral, possibly due to proper practice of preventive measures and awareness amongthe citizens including social distancing, good hygienic care and timely vaccination. Most of the cases reportedduring second wave were in the month of November/December 2020. How to cite this: Rizwan M, Naz T, Khan MB, Kang AS, Khan A, Khan T, Ali L. Prevalence of SARS-CoV-2 Infection during the COVID-19 Second Wave in Chitral, Pakistan. Life and Science. 2022; 3(3): 99-104. doi: http://doi.org/10.37185/LnS.1.1.240
Source: Life and Science
DOI: 10.37185/lns.1.1.240
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7203979449