As the world suffers from the effects of the 2019 pandemic of coronavirus infection (COVID-19), scientists around the world are conducting extensive research to better understand the disease and the dynamics of its pathogen transmission. causative: severe respiratory coronavirus syndrome 2 (SARS-CoV-2).
In a short time, they have obtained vital information about the structure and genetic sequence of SARS-CoV-2. These studies have played a vital role in determining the mutation pattern of the virus and, in turn, in the development of vaccines and other protective measures (such as anticoagulants). Identifying the association between SARS-CoV-2, demographics, and environmental factors (e.g., air quality), is important for mapping seasonal variability and carriers.
Researchers have previously reported that major demographic changes, such as ethnicity, age, gender, and population density significantly affect SARS-CoV-2 disease. A significant increase in the mortality rate from COVID-19 was associated with the older age group. This can be due to two factors, ie, low age – related immunity levels and pre – existing health conditions such as diabetes, lung disease, hip tension, etc. Although the relationship between sex and COVID-19 is not fully understood, men are reported to be more likely to suffer from SARS-CoV-2 complications and death. Scientists have also reported that some ethnic groups are at greater risk. Multiple studies have demonstrated that environmental factors and epidemiological parameters are associated with SARS-CoV-2 infection.
A new piece of research was conducted using a wide range of variables related to demographic and environmental factors in New York State (NYS), USA. NYS is made up of urban and ethnically diverse counties, some densely populated and others sparsely populated. This research was published on medRxiv* preprint server.
In this study, researchers have grouped the counties based on COVID-19 infection and mortality and linked them to different demographic and environmental variables. A recovery model was constructed to understand the contribution of these variables to SARS-CoV-2 frequency, mortality, and mortality.
For this study, researchers obtained data on COVID-19 infection rates, mortality, and mortality rates from 62 counties in NYS for the period March 1, 2020, to May 16, 2020, from available sources in public. All data were grouped by region, population over age 55, Hispanic American population, poverty rates, and African American population. The distances were measured using ArcGIS Map 10.7.1 software and the environmental factors were obtained from the Environmental Protection Agency (EPA). Data on PM2.5 was used to measure air quality. The statistical methods used to perform the comparative analysis between the various variables included the Kruskal-Wallis test, a non-parametric equivalent of a one-way analysis of variability (ANOVA), the Mann-Whitney test U, help. The ARIMA model was used to analyze multi-year temperature data.
After the first wave of the pandemic, researchers described heterogeneity, across counties, in terms of disease rate, mortality, and mortality. A strong correlation was observed between COVID-19 infection and the number of deaths. Resuscitation analysis also revealed a different contribution of air quality and different demographic variations on infection, mortality and mortality rates. These analyzes help to better understand the impact of demographic and environmental factors on COVID-19 in NYS.
Disease and mortality from COVID-19 in NYS counties (data to May 16, 2020). (AB) Disease rates (A) and (B) mortality rates in individual counties are shown; counties are grouped into three groups using k-means collection methods. (C) Maps of NYS showing the locations of the counties included in each of the collections.
Previous research has suggested a higher risk of virus exposure due to socioeconomic inequalities such as living in densely populated areas, professional demands, and a higher frequency of harmful comorbidity. Previous research has also reported that people with low socioeconomic status are more vulnerable to SARS-CoV-2 disease. The current research has revealed a positive correlation between poverty and COVID-19 infection in NYS.
Interestingly, researchers observed a strong correlation between PM2.5 and the percentage of the population belonging to African American or Hispanic American ethnicity. This can be the result of socio-economic inequality. This makes the population of African America and Hispanic America more vulnerable due to the poor air quality around them.
While studying two demographic variables, namely, distance from the primary heart and age over 55 years, researchers found that the distance of NYS counties from the disease platform is more closely related. surprising to COVID-19 disease and mortality rates.
The results of the current study are helping researchers to see the impact of COVID-19 on NYS counties. The recall model has helped assess the contribution of environmental and demographic factors to disease. A comprehensive assessment of the association of these variables with the incidence of the disease would help to better understand the impact of the disease on the population. This would also help to develop mitigation measures or prevention policies to prevent the spread of the disease.
* Important message
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be seen as final, guiding health-related clinical practice / behavior, or treated as fixed information.