Incidence dynamics and investigation of key interventions in a dengue outbreak in Ningbo City, China

Linking mathematical models and trap data to infer the proliferation, abundance, and control of Aedes aegypti

Aedes aegypti is one of the most dominant mosquito species in the urban areas of Miami-Dade County, Florida, and is responsible for the local arbovirus transmissions. Since August 2016, mosquito traps have been placed throughout the county to improve surveillance and guide mosquito control and arbovirus outbreak response. In this paper, we develop a deterministic mosquito population model, estimate model parameters by using local entomological and temperature data, and use the model to calibrate the mosquito trap data from 2017 to 2019. We further use the model to compare the Ae. aegypti population and evaluate the impact of rainfall intensity in different urban built environments. Our results show that rainfall affects the breeding sites and the abundance of Ae. aegypti more significantly in tourist areas than in residential places. In addition, we apply the model to quantitatively assess the effectiveness of vector control strategies in Miami-Dade County.

Model-based risk assessment of dengue fever transmission in Xiamen City, China

Background

Quantitative assessment of the risk of local transmission from imported dengue cases makes a great challenge to the development of public health in China. The purpose of this study is to observe the risk of mosquito-borne transmission in Xiamen City through ecological and insecticide resistance monitoring. Quantitative evaluation of mosquito insecticide resistance, community population and the number of imported cases affecting the transmission of dengue fever (DF) in Xiamen was carried out based on transmission dynamics model, so as to reveal the correlation between key risk factors and DF transmission.

Methods

Based on the dynamics model and combined with the epidemiological characteristics of DF in Xiamen City, a transmission dynamics model was built to simulate the secondary cases caused by imported cases to evaluate the transmission risk of DF, and to explore the influence of mosquito insecticide resistance, community population and imported cases on the epidemic situation of DF in Xiamen City.

Results

For the transmission model of DF, when the community population is between 10,000 and 25,000, changing the number of imported DF cases and the mortality rate of mosquitoes will have an impact on the spread of indigenous DF cases, however, changing the birth rate of mosquitoes did not gain more effect on the spread of local DF transmission.

Conclusions

Through the quantitative evaluation of the model, this study determined that the mosquito resistance index has an important influence on the local transmission of dengue fever caused by imported cases in Xiamen, and the Brayton index can also affect the local transmission of the disease.

A Review of the Surveillance Techniques for Aedes albopictus

Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) transmits a variety of arboviruses (arthropod-borne viruses) and acts as one of the most dangerous mosquito species in the world. Mosquito surveillance is the main means of evaluating vector density, vector-borne disease risk, and the efficacy of vector-control operations. The larval density of Ae. albopictus can be reflected by means of Breteau index and Route index, and egg density can be monitored by ovitrap and mosq-ovitrap, whereas mosquito surveillance methods mainly include human landing catch, human-baited double net trap, BG-Sentinel trap, autocidal gravid ovitrap, gravid Aedes trap, and mosquito magnet. This article describes different methods of Ae. albopictus surveillance and offers suggestions to improve surveillance.

Age-specific transmission dynamic of mumps: A long-term large-scale modeling study in Jilin Province, China

Objectives

Despite the adoption of a new childhood immunization program in China, the incidence of mumps remains high. This study aimed to describe the epidemiological characteristics of mumps in Jilin Province from 2005 to 2019 and to assess the transmissibility of mumps virus among the whole population and different subgroups by regions and age groups.

Methods

The Non-age-specific and age-specific Susceptible-Exposed-Pre-symptomatic-Infectious-Asymptomatic-Recovered (SEPIAR) models were fitted to actual mumps incidence data. The time-varying reproduction number (R _t ) was used to evaluate and compare the transmissibility.

Results

From 2005 to 2019, a total of 57,424 cases of mumps were reported in Jilin Province. The incidence of mumps was the highest in people aged 5 to 9 years (77.37 per 100,000). The two SEPIAR models fitted the reported data well (P < 0.01). The median transmissibility (R _t ) calculated by the two SEPIAR models were 1.096 (range: 1.911 × 10^-5-2.192) and 1.074 (range: 0.033-2.114) respectively. The age-specific SEPIAR model was more representative of the actual epidemic of mumps in Jilin Province from 2005-2019.

Conclusions

For mumps control, it is recommended that mumps-containing vaccines (MuCV) coverage be increased nationwide in the 5-9 years age group, either by a mumps vaccine alone or by a combination of vaccines such as measles-mumps-rubella (MMR) vaccine. The coverage of vaccines in Jilin Province should be continuously expanded to establish solid immunity in the population. China needs to redefine the optimal time interval for MuCV immunization.

Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

Assessing the Impacts of Meteorological Factors on COVID-19 Pandemic Using Generalized Estimating Equations

Background

Meteorological factors have been proven to affect pathogens; both the transmission routes and other intermediate. Many studies have worked on assessing how those meteorological factors would influence the transmissibility of COVID-19. In this study, we used generalized estimating equations to evaluate the impact of meteorological factors on Coronavirus disease 2019 (COVID-19) by using three outcome variables, which are transmissibility, incidence rate, and the number of reported cases.

Methods

In this study, the data on the daily number of new cases and deaths of COVID-19 in 30 provinces and cities nationwide were obtained from the provincial and municipal health committees, while the data from 682 conventional weather stations in the selected provinces and cities were obtained from the website of the China Meteorological Administration. We built a Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model to fit the data, then we calculated the transmissibility of COVID-19 using an indicator of the effective reproduction number (Reff ). To quantify the different impacts of meteorological factors on several outcome variables including transmissibility, incidence rate, and the number of reported cases of COVID-19, we collected panel data and used generalized estimating equations. We also explored whether there is a lag effect and the different times of meteorological factors on the three outcome variables.

Results

Precipitation and wind speed had a negative effect on transmissibility, incidence rate, and the number of reported cases, while humidity had a positive effect on them. The higher the temperature, the lower the transmissibility. The temperature had a lag effect on the incidence rate, while the remaining five meteorological factors had immediate and lag effects on the incidence rate and the number of reported cases.

Conclusion

Meteorological factors had similar effects on incidence rate and number of reported cases, but different effects on transmissibility. Temperature, relative humidity, precipitation, sunshine hours, and wind speed had immediate and lag effects on transmissibility, but with different lag times. An increase in temperature may first cause a decrease in virus transmissibility and then lead to a decrease in incidence rate. Also, the mechanism of the role of meteorological factors in the process of transmissibility to incidence rate needs to be further explored.

Entomological Investigation and Detection of Dengue Virus Type 1 in Aedes (Stegomyia) albopictus (Skuse) During the 2018–2020 Outbreak in Zhejiang Province, China

Mosquito-borne diseases are still threats to public health in the Zhejiang province of China. Surveillance of mosquitoes and the mosquito-borne pathogen is a vital approach for early warning, prevention, and control of the infectious disease. In this study, from 2018 to 2020, a total of 141607 female mosquitoes were caught by means of the light trap method. The main species were Culex pipiens quinquefasciatus/pallens (41.32%), Culex tritaeniorhynchus (47.6%), Aedes albopictus (2.5%), Anopheles sinensis (5.87%), Armigeres subalbatus (2.64%) and other mosquito species (0.07%). Cx. pipiens s.l. were the dominant species in two urban habitats and rural residential areas while Cx. tritaeniorhynchus was the main dominant species in the rural livestock sheds. In terms of seasonal fluctuation, Cx. pipiens s.l fluctuated at a high level from May to October. The peaks of Cx. tritaeniorhynchus, An. sinensis and Ar. subalbatus were in July. In addition, a total of 693 Ae. albopictus were collected with Biogents Mosquitaire CO₂ traps in emergency surveillance of dengue fever (DF) and screened for dengue virus infection. There were three circumstances of collection: The first: the sampling time before mosquito control during the local outbreak of DF in Lucheng of Wenzhou, 2019; The second circumstance: the sampling time after mosquito control during the local outbreak of DF of other cities in 2018-2019; The third circumstance: past DF epidemic areas the sampling time before mosquito control during the local outbreak of DF in Lucheng, Wenzhou, Zhejiang, 2019. The pools formed by mosquitoes collected in these three circumstances were 3 (6.1%), 35 (71.5%), and 11 (22.4%) respectively. Of the 49 pools tested, only one in the first circumstance was positive. The full-length dengue virus sequence of ZJWZ/2019 was obtained by sequencing and uploaded to the NCBI as number OK448162. Full-length nucleotide and amino acid homology analyses showed that ZJWZ2019 and Wenzhou DF serum isolates ZJWZ-62/2019 (MW582816) and ZJWZ-18/2019 (MW582815) had the highest homology. The analysis of full genome and E gene phylogenetic trees showed that ZJWZ2019 belonged to serotype 1, genotype I, lineage II, which was evolutionarily related to OK159963/Cambodia/2019. It implies that ZJWZ2019 originated in Cambodia. This study showed the species composition, seasonal dynamics of mosquitoes in different habitats in Zhejiang province and confirmed the role of Ae. albopictus in the transmission cycle of in outbreak of DF in the Lucheng district of Wenzhou in 2019, suggesting the importance of monitoring of vector Aedes infected dengue virus in the prevention and control of DF.

Meteorological factors and tick density affect the dynamics of SFTS in jiangsu province, China

Background

This study aimed to explore whether the transmission routes of severe fever with thrombocytopenia syndrome (SFTS) will be affected by tick density and meteorological factors, and to explore the factors that affect the transmission of SFTS. We used the transmission dynamics model to calculate the transmission rate coefficients of different transmission routes of SFTS, and used the generalized additive model to uncover how meteorological factors and tick density affect the spread of SFTS.

Methods

In this study, the time-varying infection rate coefficients of different transmission routes of SFTS in Jiangsu Province from 2017 to 2020 were calculated based on the previous multi-population multi-route dynamic model (MMDM) of SFTS. The changes in transmission routes were summarized by collecting questionnaires from 537 SFTS cases in 2018–2020 in Jiangsu Province. The incidence rate of SFTS and the infection rate coefficients of different transmission routes were dependent variables, and month, meteorological factors and tick density were independent variables to establish a generalized additive model (GAM). The optimal GAM was selected using the generalized cross-validation score (GCV), and the model was validated by the 2016 data of Zhejiang Province and 2020 data of Jiangsu Province. The validated GAMs were used to predict the incidence and infection rate coefficients of SFTS in Jiangsu province in 2021, and also to predict the effect of extreme weather on SFTS.

Results

The number and proportion of infections by different transmission routes for each year and found that tick-to-human and human-to-human infections decreased yearly, but infections through animal and environmental transmission were gradually increasing. MMDM fitted well with the three-year SFTS incidence data (P<0.05). The best intervention to reduce the incidence of SFTS is to reduce the effective exposure of the population to the surroundings. Based on correlation tests, tick density was positively correlated with air temperature, wind speed, and sunshine duration. The best GAM was a model with tick transmissibility to humans as the dependent variable, without considering lagged effects (GCV = 5.9247E-22, R² = 96%). Reported incidence increased when sunshine duration was higher than 11 h per day and decreased when temperatures were too high (>28°C). Sunshine duration and temperature had the greatest effect on transmission from host animals to humans. The effect of extreme weather conditions on SFTS was short-term, but there was no effect on SFTS after high temperature and sunshine hours.

Conclusions

Different factors affect the infection rate coefficients of different transmission routes. Sunshine duration, relative humidity, temperature and tick density are important factors affecting the occurrence of SFTS. Hurricanes reduce the incidence of SFTS in the short term, but have little effect in the long term. The most effective intervention to reduce the incidence of SFTS is to reduce population exposure to high-risk environments.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging vector-borne disease caused by SFTS virus. After the first case was detected in China in 2009, SFTS endemic areas have gradually increased, with more than 23 provinces and cities reporting SFTS cases. In order to explore the transmission mechanism of SFTS and explain the impact of meteorological factors and tick density on the transmission routes of SFTS, this study collected SFTS cases data, meteorological data and tick surveillance data in Jiangsu Province from 2017 to 2019 to investigate the study question. The multi-population and multi-route dynamic model established in the previous study was used to calculate the infection rate coefficients of various transmission routes of SFTS in Jiangsu Province, and the generalized additive model was established to further elaborate the influence of SFTS transmission mechanism.

Computing R0 of dynamic models by a definition-based method

Objectives

Computing the basic reproduction number (R₀) in deterministic dynamical models is a hot topic and is frequently demanded by researchers in public health. The next-generation methods (NGM) are widely used for such computation, however, the results of NGM are usually not to be the true R₀ but only a threshold quantity with little interpretation. In this paper, a definition-based method (DBM) is proposed to solve such a problem.

Methods

Start with the definition of R₀, consider different states that one infected individual may develop into, and take expectations. A comparison with NGM has proceeded. Numerical verification is performed using parameters fitted by data of COVID-19 in Hunan Province.

Results

DBM and NGM give identical expressions for single-host models with single-group and interactive R_ij of single-host models with multi-groups, while difference arises for models partitioned into subgroups. Numerical verification showed the consistencies and differences between DBM and NGM, which supports the conclusion that R₀ derived by DBM with true epidemiological interpretations are better.

Conclusions

DBM is more suitable for single-host models, especially for models partitioned into subgroups. However, for multi-host dynamic models where the true R₀ is failed to define, we may turn to the NGM for the threshold R₀.

Data science

Since the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China, in late December 2019, the disease has already affected over 200 countries and territories in less than 4 months. On March 11, 2020, the WHO declared the outbreak as a pandemic. As of April 25, 2020, the contagious disease has already infected over 2,919,404 people and the number of deaths reached nearly 206,482.

As the disease is spreading rapidly, very less information is available regarding the spread of the novel virus and its effect over various countries. With the help of data science and its latest applications, this chapter aims to explain the rapid spread and impact of the novel coronavirus infection over individual countries. In this chapter, we have first explained about the evolution and transmission of viral diseases from animals to humans, next discussed about the various statistical methods used for the analysis of the spread of the disease, and finally come up with a comparison of the past 2 months of the pandemic (March and April). This chapter will give an insight of the application of data science in analyzing the latest COVID-19 pandemic and its impact.

Study of COVID-19 mathematical model of fractional order via modified Euler method

Our main goal is to develop some results for transmission of COVID-19 disease through Bats-Hosts-Reservoir-People (BHRP) mathematical model under the Caputo fractional order derivative (CFOD). In first step, the feasible region and bounded ness of the model are derived. Also, we derive the disease free equilibrium points (DFE) and basic reproductive number for the model. Next, we establish theoretical results for the considered model via fixed point theory. Further, the condition for Hyers-Ulam’s (H-U) type stability for the approximate solution is also established. Then, we compute numerical solution for the concerned model by applying the modified Euler’s method (MEM). For the demonstration of our proposed method, we provide graphical representation of the concerned results using some real values for the parameters involve in our considered model.

Land use and land cover change and its impacts on dengue dynamics in China: A systematic review

Background

Dengue is a prioritized public health concern in China. Because of the larger scale, more frequent and wider spatial distribution, the challenge for dengue prevention and control has increased in recent years. While land use and land cover (LULC) change was suggested to be associated with dengue, relevant research has been quite limited. The “Open Door” policy introduced in 1978 led to significant LULC change in China. This systematic review is the first to review the studies on the impacts of LULC change on dengue dynamics in China. This review aims at identifying the research evidence, research gaps and provide insights for future research.

Methods

A systematic literature review was conducted following the PRISMA protocol. The combinations of search terms on LULC, dengue and its vectors were searched in the databases PubMed, Web of Science, and Baidu Scholar. Research conducted on China published from 1978 to December 2019 and written in English or Chinese was selected for further screening. References listed in articles meeting the inclusion criteria were also reviewed and included if again inclusion criteria were met to minimize the probability of missing relevant research.

Results

28 studies published between 1978 and 2017 were included for the full review. Guangdong Province and southern Taiwan were the major regional foci in the literature. The majority of the reviewed studies observed associations between LULC change factors and dengue incidence and distribution. Conflictive evidence was shown in the studies about the impacts of green space and blue space on dengue in China. Transportation infrastructure and urbanization were repeatedly suggested to be positively associated with dengue incidence and spread. The majority of the studies reviewed considered meteorological and sociodemographic factors when they analyzed the effects of LULC change on dengue. Primary and secondary remote sensing (RS) data were the primary source for LULC variables. In 21 of 28 studies, a geographic information system (GIS) was used to process data of environmental variables and dengue cases and to perform spatial analysis of dengue.

Conclusions

The effects of LULC change on the dynamics of dengue in China varied in different periods and regions. The application of RS and GIS enriches the means and dimensions to explore the relations between LULC change and dengue. Further comprehensive regional research is necessary to assess the influence of LULC change on local dengue transmission to provide practical advice for dengue prevention and control.

Dengue is a major public health concern in China. The rapid development of urbanization along with climate change increases the challenge for dengue prevention and control. Previous research has mainly focused on the meteorological variables whereas land use and land cover (LULC) change received comparatively less attention. Our review identified that the regional research hotspots of dengue epidemics in China were Guangdong Province and southern Taiwan. Though inconsistent, most included studies somehow observed associations between at least one of the LULC change factors and dengue. A geographical information system (GIS) was widely used to perform spatial analysis in the selected literature. Its application provided a novel view to describe the relationships between environmental factors and the situation of dengue, which enabled scholars to explore more characteristics of dengue transmission. Meanwhile, the use of remote sensing (RS) enriched the means of environmental monitoring. However, there are research gaps in the area of dengue and LULC change, such as the less consideration of dengue vector study, the lack of interplays between factors, and the lack of considering interventions and policies. Furthermore, because of different research settings, results from these studies were difficult to compare. Thus, further comprehensive and comparable investigations are necessary to better understand the effects of LULC change on dengue in China. This review is the first to expound the studies on the associations between LULC change and dengue dynamics in China. It demonstrates the findings and methodologies and provided insights for future research.

Emerging Mosquito-Borne Viruses Linked to Aedes aegypti and Aedes albopictus: Global Status and Preventive Strategies

Emerging mosquito-borne viruses continue to cause serious health problems and economic burden among billions of people living in and near the tropical belt of the world. The highly invasive mosquito species Aedes aegypti and Aedes albopictus have successively invaded and expanded their presence as key vectors of Chikungunya virus, dengue virus, yellow fever virus, and Zika virus, and that has consecutively led to frequent outbreaks of the corresponding viral diseases. Of note, these two mosquito species have gradually adapted to the changing weather and environmental conditions leading to a shift in the epidemiology of the viral diseases, and facilitated their establishment in new ecozones inhabited by immunologically naive human populations. Many abilities of Ae. aegypti and Ae. albopictus, as vectors of significant arbovirus pathogens, may affect the infection and transmission rates after a bloodmeal, and may influence the vector competence for either virus. We highlight that many collaborating risk factors, for example, the global transportation systems may result in sporadic and more local outbreaks caused by mosquito-borne viruses related to Ae. aegypti and/or Ae. albopictus. Those local outbreaks could in synergy grow and produce larger epidemics with pandemic characters. There is an urgent need for improved surveillance of vector populations, human cases, and reliable prediction models. In summary, we recommend new and innovative strategies for the prevention of these types of infections.

Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study

BACKGROUND

Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy.

METHODS

We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f).

RESULTS

Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%).

CONCLUSIONS

Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.

Dengue fever transmission between a construction site and its surrounding communities in China

BACKGROUND

Due to an increase in mosquito habitats and the lack facilities to carry out basic mosquito control, construction sites in China are more likely to experience secondary dengue fever infection after importation of an initial infection, which may then increase the number of infections in the neighboring communities and the chance of community transmission. The aim of this study was to investigate how to effectively reduce the transmission of dengue fever at construction sites and the neighboring communities.

METHODS

The Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of human and SEI model of mosquitoes were developed to estimate the transmission of dengue virus between humans and mosquitoes within the construction site and within a neighboring community, as well between each of these. With the calibrated model, we further estimated the effectiveness of different intervention scenarios targeting at reducing the transmissibility at different locations (i.e. construction sites and community) with the total attack rate (TAR) and the duration of the outbreak (DO).

RESULTS

A total of 102 construction site-related and 131 community-related cases of dengue fever were reported in our area of study. Without intervention, the number of cases related to the construction site and the community rose to 156 (TAR: 31.25%) and 10,796 (TAR: 21.59%), respectively. When the transmission route from mosquitoes to humans in the community was cut off, the number of community cases decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 60 days). If the transmission route from infectious mosquitoes in the community and that from the construction site to susceptible people on the site were cut off at the same time, the number of cases on the construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days).

CONCLUSIONS

To control the outbreak of dengue fever effectively on both the construction site and in the community, interventions needed to be made both within the community and from the community to the construction site. If interventions only took place within the construction site, the number of cases on the construction site would not be reduced. Also, interventions implemented only within the construction site or between the construction site and the community would not lead to a reduction in the number of cases in the community.

Epidemiological trends of imported infectious diseases in Japan: Analysis of imported 2-year infectious disease registry data

INTRODUCTION

The epidemiology of infectious diseases in Japan remains undefined despite the increasing tourism. GeoSentinel, an epidemiological surveillance system for reporting imported infectious diseases, has only two participating facilities in Japan. Although the number of infectious diseases is reported by the National Institute of Infectious Diseases, there is no detailed clinical information about these cases. Therefore, we established J-RIDA (Japan Registry for Infectious Diseases from Abroad) to clarify the status of imported infectious diseases in Japan and provide detailed information.

METHODS

J-RIDA was started as a registry of imported infectious diseases. Case registration began in October 2017. Between October 2017 and September 2019, 15 medical institutions participated in this clinical study. The registry collected information about the patient's age, sex, nationality, chief complaint, consultation date, date of onset, whether visit was made to a travel clinic before travel, blood test results (if samples were collected), travel history, and final diagnosis.

RESULTS

Of the 3046 cases included in this study, 46.7% to Southeast Asia, 13.0% to Africa, 13.7% to East Asia, 11.5% to South Asia, 7.5% to Europe, 3.8% to Central and South America, 4.6% to North America, 3.9% to Oceania, and 2.8% to Central and west Asia. More than 85% of chief complaints were fever and general symptoms, gastrointestinal symptoms, respiratory symptoms, or dermatologic problems. The most common diseases were travelers' diarrhea, animal bite, upper respiratory infection, influenza, and dengue fever.

CONCLUSIONS

We summarized two-year cases registered in Japan's imported infectious disease registry. These results will significantly contribute to the epidemiology in Japan.

A five-compartment model of age-specific transmissibility of SARS-CoV-2

BACKGROUND

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model.

METHODS

An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model.

RESULTS

The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: β43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: β34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: β22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: β31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: β33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: β44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: β32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: β14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: β43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: β34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8).

CONCLUSIONS

SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

The effectiveness of early start of Grade III response to dengue in Guangzhou, China: A population-based interrupted time-series study

In 2019, dengue incidences increased dramatically in many countries. However, the prospective growth in dengue incidence did not occur in Guangzhou, China. We examined the effectiveness of early start of Grade III response to dengue in Guangzhou. We extracted the data on daily number of dengue cases during 2017–2019 in Guangzhou and weekly data for Foshan and Zhongshan from the China National Notifiable Disease Reporting System, while the data on weekly number of positive ovitraps for adult and larval Aedes albopictus were obtained from Guangzhou Center for Disease Control and Prevention. We estimated the number of dengue cases prevented by bringing forward the starting time of Grade III response from September in 2017–2018 to August in 2019 in Guangzhou using a quasi-Poisson regression model and applied the Baron and Kenny’s approach to explore whether mosquito vector density was a mediator of the protective benefit. In Guangzhou, early start of Grade III response was associated with a decline in dengue incidence (relative risk [RR]: 0.54, 95% confidence interval [CI]: 0.43–0.70), with 987 (95% CI: 521–1,593) cases averted in 2019. The rate of positive ovitraps also significantly declined (RR: 0.64, 95% CI: 0.53–0.77). Moreover, both mosquito vector density and early start of Grade III response was significantly associated with dengue incidence after adjustment for each other. By comparing with the incidence in Foshan and Zhongshan where the Grade III response has not been taken, benefits from the response starting in August were confirmed but not if starting from September. Early start of Grade III response has effectively mitigated the dengue burden in Guangzhou, China, which might be partially through reducing the mosquito vector density. Our findings have important public health implications for development and implementation of dengue control interventions for Guangzhou and other locations with dengue epidemics.

There is a lack of data on comparing the observed dengue incidences under the real-world scenarios that interventions commenced at different times. In 2019, WHO scaled up the response to dengue due to the escalation of outbreaks occurring in many countries. In the same year, local government in Guangzhou started the Grade III response to dengue one month ahead in August. It is uncertain the degree to which the early intervention mitigated dengue burden. Our study examined the effectiveness of early start of Grade III response in Guangzhou using a quasi-Poisson regression model by comparing the dengue incidence with early start of Grade III response and that under the counterfactual scenario that the Grade III response began in September as in 2017 and 2018. We estimated that 987 dengue cases were averted due to the early start of Grade III response, which were equivalent to 71.4% of the total number of local dengue cases in 2019. Early start of Grade III response reduced the dengue burden, which might be partially through controlling the mosquito vector density. Dengue intervention strategies applied in Guangzhou could provide experience on how to effectively prevent and control dengue for other locations with dengue epidemics.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

Background

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus.

Methods

In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R₀) from the RP model to assess the transmissibility of the SARS-CoV-2.

Results

The value of R₀ was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.

Conclusions

Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

BACKGROUND

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus.

METHODS

In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R₀) from the RP model to assess the transmissibility of the SARS-CoV-2.

RESULTS

The value of R₀ was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.

CONCLUSIONS

Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.