Pattern and determinants of COVID-19 infection and mortality across countries: An ecological study

Abstract

Background This work aimed to identify the mathematical model and ecological pattern of COVID-19 infection and mortality across different countries during the first six months of the pandemic. Methodology In this pilot study, authors used the online available data sources of randomly selected 18 countries to collect ecological predictors of COVID-19 transmissibility and mortality. The studied determinants were environmental factors (daily average temperature, daily humidity) and socioeconomic attributes (population age structure, count and density, human development index, per capita income (PCI), gross domestic product, internet coverage, mobility trends, chronic diseases). Researchers used the linear and exponential time series analysis, and further utilize multivariate techniques to explain the variance in the monthly exponential growth rates of new cases and deaths. Result In the first two months, the R 2 of linear models for the cases and deaths were higher than that of the corresponding R 2 of the exponential model. Later one, R 2 of the exponential model was occasionally relatively higher than that of the linear models. The exponential growth rate of new cases was significantly associated with mobility trends (β=0.00398, P =0.002), temperature (β=0.000679, P =0.011), humidity (β=0.000249, P =0.000), and the proportion of patients aged above 65 years (β=-0.000959, P =0.012). Similarly, the exponential growth rate of deaths was significantly associated with mobility trends (β=0.0027, P =0.049), temperature (β=0.0014, P<0.001), humidity (β=-0.0026, P=0.000), and PCI of countries. During this period, COVID-19 transmissibility was evident to be controlled as soon as social mobility is decreased by about 40% of the baseline over 3 months controlling for the other predictors. Conclusion Controlling of COVID-19 pandemic is based mainly on controlling social mobility. Role of environmental determinants like temperature and humidity was well noticed on disease fatality and transmissibility. COVID-19 contagiousness and fatality were additionally affected by human modifiable risk factors like income and non-modifiable risk factors (ageing) affected.

The impact of access to financial services on mitigating COVID-19 mortality globally

“…Though our main interest here is not these previously studied population health and socioeconomic variables, we include some key national-level public health risk characteristics as control variables. These control variables were selected based on previous evidence in the literature as covariates with COVID-19 mortality, including population health and respiratory issues (levels of hypertension, lung cancer, tuberculosis, diabetes, obesity, and air pollution); healthcare system availability and effectiveness; and socio-economic characteristics, including age distribution, urbanization, population density, and socioeconomic inequalities (e.g., [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]).…”

GIS-Based Analysis Framework to Identify the Determinants of COVID-19 Incidence and Fatality in Africa

“…It well established that patients with comorbidities like hypertension, diabetes, bronchial asthma are more susceptible to COVID-19 related complication. 9,19 Since the number of the comorbid illnesses increases with age, another possible reason for the observed higher mortality in older patients might exist. 42 We speculate that reporting the cause of death as COVID-19 may be underestimated in African countries.…”

“…20,21 Such strategies were found to be effective to mitigate COVID-19 transmission. [22][23][24] Limiting travel was found to have modest effect while transmission reduction measures like lockdown showed higher levels of effectiveness in the disease transmission control. 25 This generally implies that population mobility is one of the main determinants of COVID-19 incidence.…”

“…In this respect, it was found that COVID-19 transmission and fatality were negatively correlated with temperature 2 and positively correlated with absolute humidity. 6,9 Also, it was, argued that air pollution can promote sustained transmission of COVID-19, where COVID-19 incidence was found to be positively correlated with atmospheric particulate matter and nitric oxide. 10 The association between the particulate matter pollution and COVID-19 case fatality rate (CFR) was emphasized as well.…”

COVID-19 Vaccine Acceptance among Social Media Users: A Content Analysis, Multi-Continent Study

“…This pandemic affected over 474.7 millions of people worldwide with over 6.1 million deaths [2]. The pattern of infection and mortality differed significantly across countries [3,4]. Healthcare workers and elderly people are at higher risk of acquiring the infection and related complications, but there is also an increase in the number of young persons who present with COVID-19 related complications [5].…”