Translating transmissibility measures into recommendations for coronavirus prevention

ABSTRACT The rapid increase in clinical cases of the new coronavirus disease, COVID-19, suggests high transmissibility. However, the estimates of the basic reproductive number reported in the literature vary widely. Considering this, we drew the function of contact-rate reduction required to control the transmission from both detectable and undetectable sources. Based on this, we offer a set of recommendations for symptomatic and asymptomatic populations during the current pandemic. Understanding the dynamics of transmission is essential to support government decisions and improve the community's adherence to preventive measures.

Epidemiological Model for Pediatrics Patients with Leprosy Infection

Leprosy Infection (LI) is a long-term chronic infectious disease caused by the bacterium Mycobacterium leprae or Mycobacterium lepromatosis. This infectious disease has caused the public issue in many countries around the globe. The disease is prevalent among the adults, although there are now cases of the minor contacting this disease through household contact which is the primary source of infection such as (babysitters, neighbors). The emerging and reemerging diseases have led to a revived interest in infectious diseases in which mathematical models have become important tools in analyzing the spread and control of infectious diseases. Mathematical models are used in comparing, planning, implementing,evaluating and optimizing various detection, prevention therapy, and control programs, the model provides conceptual results such as threshold and basic reproduction number. In this paper, the Passive Immunity Pediatrics (M) -susceptible-Exposed-infected-recovered-susceptible (MSEIRS) model was adopted to depict the spread of infections in our environment.

A quantitative study on the epidemic situation of tuberculosis based on the transmission disease dynamics in 14 prefectures of Xinjiang from 2005 to 2017 / 中国感染控制杂志

Objective To quantitatively analyze the epidemic situation of tuberculosis(TB)by modeling the data of tuberculosis in prefectures of Xinjiang,and predict the new cases of tuberculosis in prefectures of Xinjiang.Methods A dynamic model was used to fit the data of TB in 14 prefectures in Xinjiang from 2005 to 2014,the results of the fitting were verified by tuberculosis data in 2015－2017,verified results were evaluated,estimated values and basic reproductive numbers (R0)of parameters in each region were obtained,data of new TB in 2018－2022 were predic-ted.Results The verification of TB data in 2015－2017 showed that the actual values fell within the 95% confidence interval of the predictive value curve,model was fit well.R0in Southern Kashgar was 1 1.38 (95%CI:1 1.33－11.50),R0in Urumqi City in Eastern Xinjiang and Ili Kazak Autonomous Prefecture in Northern Xinjiang were 5.46 (95% CI :5.28－5.50)and 2.22 (95% CI :2.18－2.28)respectively.The epidemic situation of TB in Southern Xinjiang was more serious than that in Northern and Eastern Xinjiang,epidemic situation of TB in Kash- gar Prefecture was most serious.The predicted results showed that the number of new TB from 2018 to 2022 will slowly grow in most prefectures.Conclusion The dynamical model of TB fits well and is feasible in this study,it can be used for prediction of new TB cases,intervention and management in Southern Xinjiang should be strength-ened to control the prevalence of TB.

Modeling and simulation of transmission dynamics of syphilis in Bayinguoleng Mongolia Autonomous Prefecture of Xinjiang / 中华地方病学杂志

Objective By analyzing the data of new syphilis cases from 2008 to 2014 in Bayinguoleng Mongolia Autonomous Prefecture (Bazhou for short) of Xinjiang to further provide reference basis for setting up control strategies.Methods Using the new syphilis data reported in Bazhou of Xinjiang,we constructed a dynamic model of transmission dynamics of syphilis,and the model was simulated and quantitatively analyzed.Results The syphilis dynamical model was introduced,the methods of setting the relevant parameters were given.It was found that the established model fitted well (MA PE =1.59％,RMSPE =0.68％),and the basic reproduction number of outbreak epidemic was estimated to be R0 =1.06 (95％ CI:1.01-1.15),it was predicted that the cumulative incidence of syphilis in Bazhou was 18 145 cases by 2024.In 2023,the cumulative number of cases was 16 465,and the number of new cases reached 1 680 in 2024.The infection rate,the number of core group partners and the treatment rate were main factors influencing the prevalence of syphilis after comparison of the sensitivity of the model parameters.Conclusion There is still an upward trend in the prevalence of syphilis infection in Bazhou of Xinjiang,and relevant departments should strengthen the prevention and control measures in high-risk groups,promote the use of condoms and other comprehensive intervention measures to control the prevalence of syphilis.