Prevalence and Associated Risk Factor of COVID-19 and Impacts of Meteorological and Social Variables on Its Propagation in Punjab, Pakistan.

Arbab Saddique,Shahzada Adnan,Muhammad Hanif,Muhammad Mujeeb Khan,Shawana Sharif,Asima Azam,Habib Bokhari,Muhammad Suleman Rana

doi:10.1007/s41748-021-00218-5

Abstract

The current study identifies the spatial distribution of COVID-19 cases and its association with meteorological and social variables in Punjab (densely populated province of Pakistan). To identify the COVID-19 propagation, the weekly growth, recovery, and deaths rate have also been calculated. The geographic information system (GIS) has used to determine COVID-19 impacts on gender (male/female), age groups, and causalities over an affected population (km−2) for the period of 11th March to 12th August, 2020 in each district of province. Our results show that 43 peak days (where daily positive cases were above 900) have been observed in Punjab during 27th May to 8th July, 2020. The high population density districts, i.e., Lahore and Islamabad, have been affected (five persons per square kilometers) due to COVID-19, whereas the maximum death tolls (> 50 persons per millions) have also been observed in these urban districts. The meteorological variables (temperature, humidity, heat index, and ultraviolet index) show negative significant relationship to basic reproduction number (R0), whereas daily COVID-19 cases are positively correlated to aerosols concentration at 95% confidence level. The government intervention (stringency index) shows a positive impact to reduce the COVID-19 cases over the province. Keeping in view the COVID-19 behavior and climatology of the region, it has been identified that the COVID-19 cases may likely to increase during the dry period (high concentration of aerosols) i.e., October–December, 2020 and post-spring season (April to June), 2021 in urban areas of Pakistan. This study provides an overview on districts vulnerability that would help the policy makers, health agencies to plan their activities to reduce the COVID-19 impacts.

Highlights

The outbreak of coronavirus disease (COVID-19) has severely affected many countries of the world
Significant negative correlation has observed for temperature (− 0.36), relative humidity (RH) (− 0.33), heat index (HI) (-0.52), and ultraviolet Index (UVI) (− 0.34) to R0, whereas daily COVID-19 cases were positively correlated to aerosols (0.30) and negative to stringency index (-0.48) over Punjab province
The highest increase in the daily positive cases was observed during May–June, 2020 when RH was the lowest and aerosol concentration was highest due to dry conditions

Summary

Introduction

The outbreak of coronavirus disease (COVID-19) has severely affected many countries of the world. Several studies from Pakistan depicted that the highest number of individuals which are affected by COVID-19 belong to the 20–29 and 30–39 age groups, while the lowest are in the above 80 (Abid et al 2020; Noreen et al 2020a, b; PIDE 2020; Ladiwala et al 2021 etc.). These data seem paradoxical given that the elderly are more susceptible to the virus owing to a weakened immune system and poor health (Clark et al 2020), but this disparity can be explained by looking closely at Pakistan’s demographic and social structure. The aptitude of detection of disease pattern in different districts of Punjab would help in the efficiently planning strategies for disease control and prevention as well as provide information for further epidemiological studies to analyze disease transmission

Data and Methodology

Results and Discussion

Geo‐spatial Analysis

Impact of Weather and Government Intervention on COVID‐19

Conclusion