The coronavirus disease outbreak of 2019(COVID-19)has been spreading rapidly to all corners of the word,in a very complex manner.A key research focus is in predicting the development trend of COVID-19 scientifically t...The coronavirus disease outbreak of 2019(COVID-19)has been spreading rapidly to all corners of the word,in a very complex manner.A key research focus is in predicting the development trend of COVID-19 scientifically through mathematical modelling.We conducted a systematic review of epidemic prediction models of COVID-19 and the public health intervention strategies by searching the Web of Science database.55 studies of the COVID-19 epidemic model were reviewed systematically.It was found that the COVID-19 epidemic models were different in the model type,acquisition method,hypothesis and distribution of key input parameters.Most studies used the gamma distribution to describe the key time period of COVID-19 infection,and some studies used the lognormal distribution,the Erlang distribution,and theWeibull distribution.The setting ranges of the incubation period,serial interval,infectious period and generation time were 4.9-7 days,4.41-8.4 days,2.3-10 days and 4.4-7.5 days,respectively,and more than half of the incubation periods were set to 5.1 or 5.2 days.Most models assumed that the latent period was consistent with the incubation period.Some models assumed that asymptomatic infections were infectious or pre-symptomatic transmission was possible,which overestimated the value of R0.For the prediction differences under different public health strategies,the most significant effect was in travel restrictions.There were different studies on the impact of contact tracking and social isolation,but it was considered that improving the quarantine rate and reporting rate,and the use of protective face mask were essential for epidemic prevention and control.The input epidemiological parameters of the prediction models had significant differences in the prediction of the severity of the epidemic spread.Therefore,prevention and control institutions should be cautious when formulating public health strategies by based on the prediction results of mathematical models.展开更多
The Democratic Republic of Congo (DRC) is suffering from the world’s second largest and most prolonged Ebola virus disease (EVD) epidemic on record (Figure 1). The current prevalence of EVD in the DRC makes this the ...The Democratic Republic of Congo (DRC) is suffering from the world’s second largest and most prolonged Ebola virus disease (EVD) epidemic on record (Figure 1). The current prevalence of EVD in the DRC makes this the 10th (and largest) EVD epidemic in the DRC since the first discovery of the Zaire Ebola virus in 1976 (Ilunga Kalenga, 2019).Globally, it is the second worst outbreak in the history of Ebola epidemics.展开更多
Background:Over the past two decades,international health policies focusing on the fight against the human immunodeficiency virus/acquired immunodeficiency syndrome(HIV/AIDS),tuberculosis(TB),malaria,and those disease...Background:Over the past two decades,international health policies focusing on the fight against the human immunodeficiency virus/acquired immunodeficiency syndrome(HIV/AIDS),tuberculosis(TB),malaria,and those diseases that address maternal and child health problems,among others,have skewed disease control priorities in China and other Asian countries.Although these are important health problems,an epidemic of chronic,non-communicable diseases(NCDs)in China has accounted for a much greater burden of disease due to the ongoing rapid socioeconomic and demographic transition.Discussion:Although NCDs currently account for more than 80%of the overall disease burden in China,they remain very low on the nation’s disease control priorities,attracting marginal investment from central and local governments.This leaves the majority of patients with chronic conditions without effective treatment.International organizations and national governments have recognized the devastating social and economic consequences caused by NCDs in low-and middle-income countries,including China.Yet,few donor-funded projects that address NCDs have been implemented in these countries over the past decade.Due to a lack of strong support from international organizations and national governments for fighting against NCDs,affected persons in China,especially the poor and those who live in rural and less developed regions,continue to have limited access to the needed care.Costs associated with frequent health facility visits and regular treatment have become a major factor in medical impoverishment in China.This article argues that although China's ongoing health system reform would provide a unique opportunity to tackle current public health problems,it may not be sufficient to address the emerging threat of NCDs unless targeted steps are taken to assure that adequate financial and human resources are mapped for effective control and management of NCDs in the country.Summary:The Chinese government needs to develop a domestically-driven and evidence-based disease control policy and funding priorities that respond appropriately to the country’s current epidemiological transition,and rapid sociodemographic and lifestyle changes.展开更多
基金This work was supported by the National Natural Science Foundation of China(51778382)the National Key R&D Program of China(2016YFC0700400).
文摘The coronavirus disease outbreak of 2019(COVID-19)has been spreading rapidly to all corners of the word,in a very complex manner.A key research focus is in predicting the development trend of COVID-19 scientifically through mathematical modelling.We conducted a systematic review of epidemic prediction models of COVID-19 and the public health intervention strategies by searching the Web of Science database.55 studies of the COVID-19 epidemic model were reviewed systematically.It was found that the COVID-19 epidemic models were different in the model type,acquisition method,hypothesis and distribution of key input parameters.Most studies used the gamma distribution to describe the key time period of COVID-19 infection,and some studies used the lognormal distribution,the Erlang distribution,and theWeibull distribution.The setting ranges of the incubation period,serial interval,infectious period and generation time were 4.9-7 days,4.41-8.4 days,2.3-10 days and 4.4-7.5 days,respectively,and more than half of the incubation periods were set to 5.1 or 5.2 days.Most models assumed that the latent period was consistent with the incubation period.Some models assumed that asymptomatic infections were infectious or pre-symptomatic transmission was possible,which overestimated the value of R0.For the prediction differences under different public health strategies,the most significant effect was in travel restrictions.There were different studies on the impact of contact tracking and social isolation,but it was considered that improving the quarantine rate and reporting rate,and the use of protective face mask were essential for epidemic prevention and control.The input epidemiological parameters of the prediction models had significant differences in the prediction of the severity of the epidemic spread.Therefore,prevention and control institutions should be cautious when formulating public health strategies by based on the prediction results of mathematical models.
文摘The Democratic Republic of Congo (DRC) is suffering from the world’s second largest and most prolonged Ebola virus disease (EVD) epidemic on record (Figure 1). The current prevalence of EVD in the DRC makes this the 10th (and largest) EVD epidemic in the DRC since the first discovery of the Zaire Ebola virus in 1976 (Ilunga Kalenga, 2019).Globally, it is the second worst outbreak in the history of Ebola epidemics.
文摘Background:Over the past two decades,international health policies focusing on the fight against the human immunodeficiency virus/acquired immunodeficiency syndrome(HIV/AIDS),tuberculosis(TB),malaria,and those diseases that address maternal and child health problems,among others,have skewed disease control priorities in China and other Asian countries.Although these are important health problems,an epidemic of chronic,non-communicable diseases(NCDs)in China has accounted for a much greater burden of disease due to the ongoing rapid socioeconomic and demographic transition.Discussion:Although NCDs currently account for more than 80%of the overall disease burden in China,they remain very low on the nation’s disease control priorities,attracting marginal investment from central and local governments.This leaves the majority of patients with chronic conditions without effective treatment.International organizations and national governments have recognized the devastating social and economic consequences caused by NCDs in low-and middle-income countries,including China.Yet,few donor-funded projects that address NCDs have been implemented in these countries over the past decade.Due to a lack of strong support from international organizations and national governments for fighting against NCDs,affected persons in China,especially the poor and those who live in rural and less developed regions,continue to have limited access to the needed care.Costs associated with frequent health facility visits and regular treatment have become a major factor in medical impoverishment in China.This article argues that although China's ongoing health system reform would provide a unique opportunity to tackle current public health problems,it may not be sufficient to address the emerging threat of NCDs unless targeted steps are taken to assure that adequate financial and human resources are mapped for effective control and management of NCDs in the country.Summary:The Chinese government needs to develop a domestically-driven and evidence-based disease control policy and funding priorities that respond appropriately to the country’s current epidemiological transition,and rapid sociodemographic and lifestyle changes.
