Assessment of Epidemiological Determinants of COVID-19 Pandemic Related to Social and Economic Factors Globally

Abstract

The COVID-19 pandemic has manifested more than a health crisis and has severely impacted on social, economic, and development crises in the world. The relationship of COVID-19 with countries’ economic and other demographic statuses is an important criterion with which to assess the impact of this current outbreak. Based on available data from the online platform, we tested the hypotheses of a country’s economic status, population density, the median age of the population, and urbanization pattern influence on the test, attack, case fatality, and recovery rates of COVID-19. We performed correlation and multivariate multinomial regression analysis with relative risk ratio (RRR) to test the hypotheses. The correlation analysis showed that population density and test rate had a significantly negative association (r = −0.2384, p = 0.00). In contrast, the median age had a significant positive correlation with recovery rate (r = 0.4654, p = 0.00) and case fatality rate (r = 0.2847, p = 0.00). The urban population rate had a positive significant correlation with recovery rate (r = 0.1610, p = 0.04). Lower-middle-income countries had a negative significant correlation with case fatality rate (r= −0.3310, p = 0.04). The multivariate multinomial logistic regression analysis revealed that low-income countries are more likely to have an increased risk of case fatality rate (RRR = 0.986, 95% Confidence Interval; CI = 0.97−1.00, p < 0.05) and recovery rate (RRR = 0.967, 95% CI = 0.95–0.98, p = 0.00). The lower-income countries are more likely to have a higher risk in case of attack rate (RRR = 0.981, 95% CI = 0.97–0.99, p = 0.00) and recovery rate (RRR = 0.971, 95% CI = 0.96–0.98, p = 0.00). Similarly, upper middle-income countries are more likely to have higher risk in case of attack rate (RRR = 0.988, 95% CI = 0.98–1.0, p = 0.01) and recovery rate (RRR = 0.978, 95% CI = 0.97–0.99, p = 0.00). The low- and lower-middle-income countries should invest more in health care services and implement adequate COVID-19 preventive measures to reduce the risk burden. We recommend a participatory, whole-of-government and whole-of-society approach for responding to the socio-economic challenges of COVID-19 and ensuring more resilient and robust health systems to safeguard against preventable deaths and poverty by improving public health outcomes.

Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China

“…Previous studies have indicated that the epidemic intensity had trivial dependencies on population scale [2,23]. In order to reduce this effect, the daily confirmed cases and deaths in population size of 100,000 were set as the initial data for data processing.…”

“…These make population density and the amount of interactions with other people in super large-and very large-sized cities are higher than those of other cities [45]. According to the theory of infectious disease, the increases of population density and the amount of interactions with other people will improve the transmission risk of the epidemic [2,23,39,46]. As a result, novel coronavirus would spread faster in super large-and very large-sized cities, resulting in the large number of CCOPSPTT.…”

“…Confirmed cases and deaths of COVID-19 among different cities may be affected by socioeconomic determinants [13,22]. Virus infection is usually presented at a higher risk in large cities, because of enhanced virus spread caused by larger people mobility [12,23]. Economically underdeveloped cities could invest little in prevention to the spread of virus, thus increasing the number of virus-infected people [13,22,24].…”

Impact of Covid-19 Pandemic on Air Transport: Overview and Implications

“…Indeed, the effects of the restrictions imposed by the national governments pushed the global economy into the worst recession since the Second World War. Initially, it was the supply shock that concerned the Chinese market (along with conspicuously significant consequences on the international market as well), although the rapid spread of the virus later caused a dramatic decline in demand as well, which deeply disrupted the consumption patterns and investments in every region in the world [7][8][9][10][11].…”

Cost-Effectiveness Analysis of COVID-19 Case Quarantine Strategies in Two Australian States: New South Wales and Western Australia

“…Zhu et al (2020) reported that children are the index case of only three out of 31 household clusters. Conversely, adult cases have shown higher probabilities of hospitalisation and a need for an ICU bed as well as case fatality rates partially due to compromised immune system with age, meaning they are more likely to suffer from COVID-19 (Gao et al 2020;Hassan et al 2020). According to Verity et al (2020), on which Ferguson et al (2020) based their simulation model, the hospitalisation and case fatality rate increases with age in China.…”