ABSTRACT
The COVID-19 pandemic has significantly affected the psychological stability of general population of Pakistan. However, research on the severity of COVID-19 induced depression, anxiety, and stress (DAS) in Pakistan is scarce. This paper thereby investigates the severity of COVID-19 induced DAS based on demographic, socioeconomic, and personal feeling variables by modeling DAS. Snowball sampling strategy was adopted to conduct online survey from July 03, 2021 to July 09, 2021. Out of 2,442, 2,069 responses from Karachi were included. Descriptive and inferential statistics (binary and multinomial logistic regression analysis) were performed using SPSS V21 (IBM, 2013) to identify significant determinants and their association with DAS severity. The result of this study indicates 27.8, 21.7, and 18.3% respondents suffer from severe and extremely severe states of depression, anxiety, and stress, respectively. Binary logistic regression revealed that age is a significant determinant with odds of having 4.72 (95% CI = 1.86-11.97) and 5.86 (95% CI = 2.26-15.2) times greater depression, and stress for respondents aged 19-26 years. Moreover, gender-based difference is also observed with females 1.34 (95% CI = 1.08-1.68) and 1.75 (95% CI = 1.40-2.20) times more likely to exhibit anxiety and stress than males. Furthermore, marital status is a significant determinant of depression with odds of having depression is 0.67 (95% CI = 0.48-0.93) times greater for married population. Multinomial logistic regression revealed that those who believe COVID-19 pandemic has affected them mentally, fear new COVID-19 cases and deaths, depressed due to imposition of lockdown, believe they will not survive COVID-19 infection, and spend more time on social media gathering COVID-19 updates suffer from extremely severe state of depression (OR mental-effect-of-pandemic = 3.70, OR new-COVID-19-cases-and-deaths = 2.20, OR imposition-of-lockdown = 17.77, OR survival-probability = 8.17, OR time-on-social-media = 9.01), anxiety (OR mental-effect-of-pandemic = 4.78, OR new-COVID-19-cases-and-deaths = 3.52, OR imposition-of-lockdown = 5.06, OR survival-probability = 8.86, OR time-on-social-media = 5.12) and stress (OR mental-effect-of-pandemic = 6.07, OR imposition-of-lockdown = 11.38, OR survival-probability = 15.66, OR time-on-social-media = 4.39). Information regarding DAS severity will serve as a platform for research centers and psychological clinics, to work collectively and provide technology-based treatment to reduce the burden on the limited number of psychologist and psychotherapist.
ABSTRACT
The province of Sindh reported the first COVID-19 case in Pakistan on 26th February 2020. The Government of Sindh has employed numerous control measures to limit its spread. However, for low-and middle-income countries such as Pakistan, the management protocols for controlling a pandemic are not always as definitive as they would be in other developed nations. Given the dire socio-economic conditions of Sindh, continuation of province-wise lockdowns may inadvertently cause a potential economic breakdown. By using a data driven SEIR modelling framework, this paper describes the evolution of the epidemic projections because of government control measures. The data from reported COVID-19 prevalence and google mobility is used to parameterize the model at different time points. These time points correspond to the government's call for advice on the prerequisite actions required to curtail the spread of COVID-19 in Sindh. Our model predicted the epidemic peak to occur by 18th June 2020 with approximately 3500 reported cases at that peak, this projection correlated with the actual recorded peak during the first wave of the disease in Sindh. The impact of the governmental control actions and religious ceremonies on the epidemic profile during this first wave of COVID-19 are clearly reflected in the model outcomes through variations in the epidemic peaks. We also report these variations by displaying the trajectory of the epidemics had the control measures been guided differently; the epidemic peak may have occurred as early as the end of May 2020 with approximately 5000 reported cases per day had there been no control measures and as late as August 2020 with only around 2000 cases at the peak had the lockdown continued, nearly flattening the epidemic curve.