Assessing dengue control in Tokyo, 2014

Role of vector phenotypic plasticity in disease transmission as illustrated by the spread of dengue virus by Aedes albopictus

The incidence of vector-borne disease is on the rise globally, with burdens increasing in endemic countries and outbreaks occurring in new locations. Effective mitigation and intervention strategies require models that accurately predict both spatial and temporal changes in disease dynamics, but this remains challenging due to the complex and interactive relationships between environmental variation and the vector traits that govern the transmission of vector-borne diseases. Predictions of disease risk in the literature typically assume that vector traits vary instantaneously and independently of population density, and therefore do not capture the delayed response of these same traits to past biotic and abiotic environments. We argue here that to produce accurate predictions of disease risk it is necessary to account for environmentally driven and delayed instances of phenotypic plasticity. To show this, we develop a stage and phenotypically structured model for the invasive mosquito vector, Aedes albopictus, and dengue, the second most prevalent human vector-borne disease worldwide. We find that environmental variation drives a dynamic phenotypic structure in the mosquito population, which accurately predicts global patterns of mosquito trait-abundance dynamics. In turn, this interacts with disease transmission to capture historic dengue outbreaks. By comparing the model to a suite of simpler models, we reveal that it is the delayed phenotypic structure that is critical for accurate prediction. Consequently, the incorporation of vector trait relationships into transmission models is critical to improvement of early warning systems that inform mitigation and control strategies.

Spatiotemporal analysis of imported and local dengue virus and cases in a metropolis in Southwestern China, 2013-2022

Dengue fever is a viral illness, mainly transmitted by Aedes aegypti and Aedes albopictus. With climate change and urbanisation, more urbanised areas are becoming suitable for the survival and reproduction of dengue vector, consequently are becoming suitable for dengue transmission in China. Chongqing, a metropolis in southwestern China, has recently been hit by imported and local dengue fever, experiencing its first local outbreak in 2019. However, the genetic evolution dynamics of dengue viruses and the spatiotemporal patterns of imported and local dengue cases have not yet been elucidated. Hence, this study implemented phylogenetic analyses using genomic data of dengue viruses in 2019 and 2023 and a spatiotemporal analysis of dengue cases collected from 2013 to 2022. We sequenced a total of 15 nucleotide sequences of E genes. The dengue viruses formed separate clusters and were genetically related to those from Guangdong Province, China, and countries in Southeast Asia, including Laos, Thailand, Myanmar and Cambodia. Chongqing experienced a dengue outbreak in 2019 when 168 imported and 1,243 local cases were reported, mainly in September and October. Few cases were reported in 2013-2018, and only six were imported from 2020 to 2022 due to the COVID-19 lockdowns. Our findings suggest that dengue prevention in Chongqing should focus on domestic and overseas population mobility, especially in the Yubei and Wanzhou districts, where airports and railway stations are located, and the period between August and October when dengue outbreaks occur in endemic regions. Moreover, continuous vector monitoring should be implemented, especially during August-October, which would be useful for controlling the Aedes mosquitoes. This study is significant for defining Chongqing's appropriate dengue prevention and control strategies.

Green cities and vector-borne diseases: emerging concerns and opportunities

Aligned with the Sustainable Development Goals, nature-based solutions such as urban greening e.g. public gardens, urban forests, parks and street trees, which aim to protect, sustainably manage or restore an ecosystem, have emerged as a promising tool for improving the health and well-being of an ever-increasing urban population. While urban greening efforts have undeniable benefits for human health and the biological communities inhabiting these green zones, disease vector populations may also be affected, possibly promoting greater pathogen transmission and the emergence of infectious diseases such as dengue, West Nile fever, malaria, leishmaniosis and tick-borne diseases. Evidence for the impact of urban green areas on vector-borne disease (VBD) transmission is scarce. Furthermore, because of vast disparities between cities, variation in green landscapes and differing scales of observation, findings are often contradictory; this calls for careful assessment of how urban greening affects VBD risk. Improved understanding of the effect of urban greening on VBDs would support planning, monitoring and management of green spaces in cities to sustainably mitigate VBD risks for surrounding urban populations.

Reconstruction and analysis of the transmission network of African swine fever in People's Republic of China, August 2018-September 2019

Introduction of African swine fever (ASF) to China in mid-2018 and the subsequent transboundary spread across Asia devastated regional swine production, affecting live pig and pork product-related markets worldwide. To explore the spatiotemporal spread of ASF in China, we reconstructed possible ASF transmission networks using nearest neighbour, exponential function, equal probability, and spatiotemporal case-distribution algorithms. From these networks, we estimated the reproduction numbers, serial intervals, and transmission distances of the outbreak. The mean serial interval between paired units was around 29 days for all algorithms, while the mean transmission distance ranged 332 -456 km. The reproduction numbers for each algorithm peaked during the first two weeks and steadily declined through the end of 2018 before hovering around the epidemic threshold value of 1 with sporadic increases during 2019. These results suggest that 1) swine husbandry practices and production systems that lend themselves to long-range transmission drove ASF spread; 2) outbreaks went undetected by the surveillance system. Efforts by China and other affected countries to control ASF within their jurisdictions may be aided by the reconstructed spatiotemporal model. Continued support for strict implementation of biosecurity standards and improvements to ASF surveillance is essential for halting transmission in China and spread across Asia.

Factors affecting the transmission of dengue fever in Haikou city in 2019

In this study, due to multiple cases of dengue fever in two locations in Haikou, Hainan, several factors affecting the transmission of dengue fever in Haikou in 2019 were analyzed. It was found that dengue fever spread from two sites: a construction site, which was an epidemic site in Haikou, and the university, where only four confirmed cases were reported. Comparative analysis revealed that the important factors affecting the spread of dengue fever in Haikou were environmental hygiene status, knowledge popularization of dengue fever, educational background, medical insurance coverage and free treatment policy knowledge and active response by the government.

Quantifying the future risk of dengue under climate change in Japan

Background

In metropolitan Tokyo in 2014, Japan experienced its first domestic dengue outbreak since 1945. The objective of the present study was to quantitatively assess the future risk of dengue in Japan using climate change scenarios in a high-resolution geospatial environment by building on a solid theory as a baseline in consideration of future adaptation strategies.

Methods

Using climate change scenarios of the Model for Interdisciplinary Research on Climate version 6 (MIROC6), representative concentration pathway (RCP) 2.6, 4.5, and 8.5, we computed the daily average temperature and embedded this in the effective reproduction number of dengue, R(T), to calculate the extinction probability and interepidemic period across Japan.

Results

In June and October, the R(T) with daily average temperature T, was <1 as in 2022; however, an elevation in temperature increased the number of days with R(T) >1 during these months under RCP8.5. The time period with a risk of dengue transmission gradually extended to late spring (April–May) and autumn (October–November). Under the RCP8.5 scenario in 2100, the possibility of no dengue-free months was revealed in part of southernmost Okinawa Prefecture, and the epidemic risk extended to the entire part of northernmost Hokkaido Prefecture.

Conclusion

Each locality in Japan must formulate action plans in response to the presented scenarios. Our geographic analysis can help local governments to develop adaptation policies that include mosquito breeding site elimination, distribution of adulticides and larvicides, and elevated situation awareness to prevent transmission via bites from Aedes vectors.

The Epidemic Risk of Dengue Fever in Japan: Climate Change and Seasonality

Dengue fever is a leading cause of illness and death in the tropics and subtropics, and the disease has become a threat to many nonendemic countries where the competent vectors such as Aedes albopictus and Aedes aegypti are abundant. The dengue epidemic in Tokyo, 2014, poses the critical importance to accurately model and predict the outbreak risk of dengue fever in nonendemic regions. Using climatological datasets and traveler volumes in Japan, where dengue was not seen for 70 years by 2014, we investigated the outbreak risk of dengue in 47 prefectures, employing the temperature-dependent basic reproduction number and a branching process model. Our results show that the effective reproduction number varies largely by season and by prefecture, and, moreover, the probability of outbreak if an untraced case is imported varies greatly with the calendar time of importation and location of destination. Combining the seasonally varying outbreak risk with time-dependent traveler volume data, the unconditional outbreak risk was calculated, illustrating different outbreak risks between southern coastal areas and northern tourist cities. As the main finding, the large travel volume with nonnegligible risk of outbreak explains the reason why a summer outbreak in Tokyo, 2014, was observed. Prefectures at high risk of future outbreak would be Tokyo again, Kanagawa or Osaka, and highly populated prefectures with large number of travelers.

Analysis of international traveler mobility patterns in Tokyo to identify geographic foci of dengue fever risk

Travelers play a role in triggering epidemics of imported dengue fever because they can carry the virus to other countries during the incubation period. If a traveler carrying dengue virus visits open green space and is bitten by mosquitoes, a local outbreak can ensue. In the present study, we aimed to understand the movement patterns of international travelers in Tokyo using mobile phone data, with the goal of identifying geographical foci of dengue transmission. We analyzed datasets based on mobile phone access to WiFi systems and measured the spatial distribution of international visitors in Tokyo on two specific dates (one weekday in July 2017 and another weekday in August 2017). Mobile phone users were classified by nationality into three groups according to risk of dengue transmission. Sixteen national parks were selected based on their involvement in a 2014 dengue outbreak and abundance of Aedes mosquitoes. We found that not all national parks were visited by international travelers and that visits to cemeteries were very infrequent. We also found that travelers from countries with high dengue prevalence were less likely to visit national parks compared with travelers from dengue-free countries. Travelers from countries with sporadic dengue cases and countries with regional transmission tended to visit common destinations. By contrast, the travel footprints of visitors from countries with continuous dengue transmission were focused on non-green spaces. Entomological surveillance in Tokyo has been restricted to national parks since the 2014 dengue outbreak. However, our results indicate that areas subject to surveillance should include both public and private green spaces near tourist sites.

Measles and Rubella during COVID-19 Pandemic: Future Challenges in Japan

The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted essential health services. Simultaneously, it has created opportunities for citizens to raise awareness of personal hygiene, mask wearing, and other preventive measures. This brief report aims to clarify the epidemiological trends of measles and rubella in Japan and to explore future challenges for controlling these diseases during and after the COVID-19 pandemic. Although Japan eliminated measles in 2015, the number of measles patients has gradually increased since then, and reached 744 in 2019. In the 2010s, Japan experienced two large rubella epidemics, and the majority of the patients were reported in Tokyo and other metropolitan areas. While the transmission of measles and rubella seems to be suppressed during the COVID-19 pandemic, closing the gap in routine childhood vaccination will be challenging in any country. Moreover, supplementary immunization campaigns for adults have also been disrupted, and they must be invigorated. While the pandemic has a devastating effect on a global scale, it should be utilized as a good opportunity to regain faith in vaccines, implement an evidence-based vaccination policy, and strengthen international cooperation.

Transmission Network of Measles During the Yamagata Outbreak in Japan, 2017

Background

A measles outbreak involving 60 cases occurred in Yamagata, Japan in 2017. Using two different mathematical models for different datasets, we aimed to estimate measles transmissibility over time and explore any heterogeneous transmission patterns.

Methods

The first model relied on the temporal distribution for date of illness onset for cases, and a generation-dependent model was applied to the data. Another model focused on the transmission network. Using the illness-onset date along with the serial interval and geographical location of exposure, we reconstructed a transmission network with 19 unknown links. We then compared the number of secondary transmissions with and without clinical symptoms or laboratory findings.

Results

Using a generation-dependent model (assuming three generations other than the index case), the reproduction number (R) over generations 0, 1, and 2 were 25.3, 1.3, and <0.1, respectively, explicitly yielding the transmissibility over each generation. The network data enabled us to demonstrate that both the mean and the variance for the number of secondary transmissions per primary case declined over time. Comparing primary cases with and without secondary transmission, high viral shedding was the only significant determinant (P < 0.01).

Conclusions

The R declined abruptly over subsequent generations. Use of network data revealed the distribution of the number of secondary transmissions per primary case and also allowed us to identify possible secondary transmission risk factors. High viral shedding from the throat mucosa was identified as a potential predictor of secondary transmission.

Identifying geographic areas at risk of rubella epidemics in Japan using seroepidemiological data

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Seroepidemiological data enabled us to compute the effective reproduction number.

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Risks of a major epidemic were high in areas with capital cities.

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Urban geographic areas possess small epidemic risk due to low volume of travelers.

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Urban areas have a large number of susceptible adult males aged 30–59 years.

Objective

Even with relatively high vaccination coverage, Japan experienced rubella epidemics in 2012–2014 and 2018–2019, which were fueled by untraced imported cases. We aimed to develop a risk map for rubella epidemics in Japan by geographic location via analysis of seroepidemiological data and accounting for the abundance of foreign visitors.

Methods

Geographic age distribution and seroprevalence were used to compute the age- and sex-dependent next-generation matrix in each region. We computed the probability of a major epidemic using the assumed number of untraced imported rubella cases proportionally modeled to the number of foreign travelers.

Results

Risks of a major epidemic were high in areas with capital cities, while areas with a greater fraction of older people yielded smaller effective reproduction numbers, a lower volume of foreign travelers, and thus a lower probability of a major epidemic. The volume of susceptible adult males was larger in urban geographic regions, having a greater number of foreign travelers than remote areas.

Conclusions

Our findings are consistent with the observation of multiple large clusters of rubella cases in urban areas during 2012–2014 and 2018–2019. Should a future rubella epidemic occur, it will likely be in geographic areas with capital cities.

A Two-Patch Mathematical Model for Temperature-Dependent Dengue Transmission Dynamics

Dengue fever has been a threat to public health not only in tropical regions but non-tropical regions due to recent climate change. Motivated by a recent dengue outbreak in Japan, we develop a two-patch model for dengue transmission associated with temperature-dependent parameters. The two patches represent a park area where mosquitoes prevail and a residential area where people live. Based on climate change scenarios, we investigate the dengue transmission dynamics between the patches. We employ an optimal control method to implement proper control measures in the two-patch model. We find that blockage between two patches for a short-term period is effective in a certain degree for the disease control, but to obtain a significant control effect of the disease, a long-term blockage should be implemented. Moreover, the control strategies such as vector control and transmission control are very effective, if they are implemented right before the summer outbreak. We also investigate the cost-effectiveness of control strategies such as vaccination, vector control and virus transmission control. We find that vector control and virus transmission control are more cost-effective than vaccination in case of Korea.

Initial Cluster of Novel Coronavirus (2019-nCoV) Infections in Wuhan, China Is Consistent with Substantial Human-to-Human Transmission

Reanalysis of the epidemic curve from the initial cluster of cases with novel coronavirus (2019-nCoV) in December 2019 indicates substantial human-to-human transmission. It is possible that the common exposure history at a seafood market in Wuhan originated from the human-to-human transmission events within the market, and the early, strong emphasis that market exposure indicated animal-to-human transmission was potentially the result of observer bias. To support the hypothesis of zoonotic origin of 2019-nCoV stemming from the Huanan seafood market, the index case should have had exposure history related to the market and the virus should have been identified from animals sold at the market. As these requirements remain unmet, zoonotic spillover at the market must not be overemphasized.