A Path Analysis of Covid-19 With the Influence of Air Pressure, Air Temperature, and Relative Humidity

Abstract

Coronavirus disease 2019 (COVID-19) is one of the most infectious diseases and one of the greatest challenge due to global health crisis. The virus has been transmitted globally and spreading so fast with high incidence. While, the virus still pandemic, the government scramble to seek antiviral treatment and vaccines to combat the diseases. This study was conducted to investigate the influence of air pressure, air temperature, and relative humidity on the number of confirmed cases in COVID-19. Based on the result, the calculation of reproduced correlation through path decompositions and subsequent comparison to the empirical correlation indicated that the path model fits the empirical data. The identified factor significantly influenced the number of confirmed cases of COVID-19. Therefore, the number of daily confirmed cases of COVID-19 may reduce as the amount of relative humidity increases; relative humidity will increase as the amount of air temperature decreases; and the amount of air temperature will decrease as the amount of air pressure decreases. Thus, it is recommended that policy-making bodies consider the result of this study when implementing programs for COVID-19 and increase public awareness on the effects of weather condition, as it is one of the factors to control the number of COVID-19 cases.

Do Old Age and Comorbidity via Non-Communicable Diseases Matter for COVID-19 Mortality? A Path Analysis

“…The broad literature of COVID-19 can be classified into three types: identifying the determinants of death rate or mortality (2)(3)(4)(5)(6)(7)(8), identifying the determinants of transmission (1,(9)(10)(11)(12), and identifying the economic, social, environmental and ecological impact of COVID-19 (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22). However, these are primarily socio-economic studies related to COVID-19, which do not include a vast medical literature that focuses on the scientific causes, vulnerability, and overall health impact.…”

“…The path modeling approach has been used in the literature of transmission modeling ( 1 ), studies on psychological well-being ( 14 ), and other areas, but it has not been used in the context of COVID-19 death modeling which was mainly dominated by multiple regression and simple hypothesis testing. We used two versions of path models: first, the old age model, which focused on the demographic structure of a nation having an impact on COVID-19 deaths after controlling for other factors; second, we used another prominent model, which was known as mortality via non-communicable diseases such as cancer, heart diseases, respiratory problems, diabetes.…”

A panel path analysis approach to the determinants of coronavirus disease 2019 transmission: does testing matter for confirmed cases?

“…Suppose, we classify studies according to countries, areas or geographic regions, in that case, we find that the areas covered so far are UK, US, Canada, Iran, Chile, Germany and three to four multicounty studies and some county-level studies based on primary or secondary data. The methodologies used so far are cross-section based path models for environmental or ecological impact (Pizon et al, 2020), the effect of COVID-19 transmission on Iranian women's tension or anxiety (Zahra et al 2020). Other studies use some socioeconomic determinants on a limited scale, such as environmental or ecological factors, purely medical factors, psychological, gender, cultural, commercial, genetic or racial determinants of COVID-19 transmission (Araneda et al, 2020;Beech et al, 2020;Chang et al, 2020;Curley, 2020;Eslami and Jalill, 2020;Felbermayr et al, 2020;Fukul and Furukawa, 2020;George, 2020;Hyder et al, 2020;Kenyon, 2020;Public Health Ontario, 2020;Ontario Hospital Association, 2020;Priyadarsini and Suresh, 2020;Robertson, 2020;Roy and Khalse, 2020;Steffon, 2020;Stojkoski et al, 2020;WHO, 2020;Yamey and Gonsalves, 2020;Zyl-Smit, 2020).…”

“…A few numbers of models have been tested to observe the robustness of our result. Let us start with a typical set of equations in the modified form of Pizon et al (2020) as follows: We also allow a favorable covariance structure between the per capita GDP and A65 by the curved arrow in the estimated path. The one-way arrow represents the direction of causality as per the existing literature.…”

“…A limited number of studies are available to examine the impact of environmental factors on COVID-19 transmission by using path analysis in a cross-sectional setup by presenting the case that air pressure, air temperature and relative humidity lower the transmission of COVID-19 (Pizon et al, 2020). Pizon et al (2020) are unique contributions because it has aptly articulated the interdependence of several environmental variables in determining the transmission of COVID-19 for the Philippines in a cross-sectional framework by using the path model. The model could further be extended to other areas of COVID-19 transmission, which comes from the economic, social, political or governance perspectives.…”