Risk assessment of novel coronavirus COVID-19 outbreaks in the border areas of southwest China

Abstract

This study aimed to assess the risk of coronavirus disease 2019 in the border areas of southwest China, so as to provide guidance to targeted prevention and control measures in the border areas of different risk levels. We assessed the dependence of the risk of an outbreak in the southwest China from imported cases on key parameters such as the cumulative number of infectious diseases in the border area of southwest China in the past 3 years; the connectivity of the neighboring countries with China's Southwest border, including baseline travel numbers, travel frequencies, the effect of travel restrictions, and the length of borders with neighboring countries; the cumulative number of close contacts of coronavirus disease 2019 patients; (iv) the population density in border areas; the efficacy of control measures in border areas; experts estimated risks in border areas based on experience and then given a score; Spearman correlation and Logistic regression models were used to analyze the associated factors of novel coronavirus. According to the correlation of various factors, we assigned values to each parameter, calculated the risk score of each county, and then divided each county into high, medium, and low risk according to the sick score and took different control measure according to different risk levels. Finally, the total risk level was evaluated according to the Harvard disease risk index model. The number of infectious diseases in the past 3 years, travel numbers, travel frequencies, experts estimated risk score, effect of travel restrictions, and the number of close contacts were associated with the incidence of new coronary pneumonia. It is concluded that bilateral transportation convenience is a risk factor for new coronary pneumonia, (odds ratio = 9.23, 95% confidence interval, 1.99-42.73); the number of observers is a risk factor for new coronary pneumonia (odds ratio = 1.04, 95% confidence interval, 1.00-1.08). We found that in countries with travel numbers, travel frequencies, and experts' estimated risk scores were the influencing factors of novel coronavirus. The effect of travel restrictions and the cumulative number of close contacts of the case are risk factors for novel coronavirus.

Figure 1.

The risk map of input COVID-19 in 25 border counties (cities) in Yunnan. COVID-19 = coronavirus disease 2019.

Figure 2.

Influencing factors of incidence by binary logistic regression: travel frequencies (<1 in contrast to >4), close contacts (<1 in contrast to >367), and control capacity (<1 in contrast to >7).