Topic : Statistical methods used to assess impacts of socio-ecological factors on COVID-19 incidence: a systematic review
Abstract
Environmental and socio-demographic factors may interact to accelerate or reduce dynamics of epidemics such as the COVID-19. To understand the effects of such factors on the COVID-19, several studies have used diverse statistical methods to address the issue, but we still lack a quantitative synthesis of these research works. This study performed a global systematic review on (i) statistical methods used to assess impacts of socio-ecological factors on COVID-19 incidence, (ii) the most assessed socio-ecological factors, and (iii) the direction (positive, neutral, or negative) of the effects of socio-ecological factors on the disease dynamics. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used. Relevant scientific databases, such as Pubmed, Google Scholar, NCBI, Science-Direct were considered to search for articles on the modelling of socio-ecological factors affecting COVID-19 incidence. From an initial collection of 31,849 articles, 315 were included based on eligibility criteria and after removing duplicates. Results showed that most of studies (51.11 %) have a country scope. The largest number of studies on COVID-19 cases covered Asian continent while most studies on COVID-19 deaths covered American continent. The most used response variables were the daily new cases of COVID-19 and the daily number of COVID-19 deaths. The most widely used statistical methods were Pearson correlation analysis (15.23%), Simple and multiple linear regression analysis (12.44%), descriptive statistics (12.23%), Poisson regression analysis (9.44 %), Multivariable logistic regression (8.79%). A total of 216 socio-ecological factors were assessed among which 24.65% were socio-economics and political factors, 25.12 % were health factors, 20.0 % were related to demographic factors, 13.02 % were climatic/environmental factors, 8.84% were migration and transport factors and 8.37 % were chemical pollutants. Concerning the direction, the effect of socio-ecological factors was not unique, but rather mixed. For instance, 45.76% of studies found negative effect of temperature on COVID-19 incidence while 34.74 % found positive effect and 19.49% showed neutral effect. The same is true for the age factor where 65.85% of studies showed a positive correlation with COVID-19 incidence, 2.87% affirmed a negative correlation and 29.26% a neutral effect. Also, 80.64% of studies found a positive effect of comorbidities on COVID-19 incidence against 19.35% which demontrated a neutral effect. These results may be useful for defining measures to reduce the expansion of COVID-19 and also for future studies on modeling dynamics of COVID-19 in the socio-ecological context of Africa.
Keywords: Systematic review, statistical methods, socio-ecological factors, COVID-19 incidence.