The threat of climate change to non-dengue-endemic countries: increasing risk of dengue transmission potential using climate and non-climate datasets

Tropical Diseases in Okinawa: Overview and Emerging Infectious Diseases

Okinawa prefecture is at risk for emerging infectious diseases due to its subtropical climate and its location within the Indo-Pacific region. Understanding the existing vectors and infectious agents contextualizes current threats, guides treatment, and informs prevention, and may be of unique concern in the setting of complex emergencies.

Insights from multigene analysis: first report of a Southeast Asian Mosquito, Aedes (Mucidus) laniger (Diptera: Culicidae) on Jeju Island from Korea

BACKGROUND

Certain mosquitoes are known as dominant vectors worldwide, and transmit infectious diseases. The expansion of mosquito habitats due to climate change and increased human activities poses a significant health threat by facilitating the spread of various non-native infectious diseases. This study focused on the detection of the Southeast Asian mosquito species, Aedes (Mucidus) laniger (Wiedemann, 1820) on Jeju Island, the southernmost region of the Republic of Korea (ROK), highlighting the potential risks associated with the spread of vector-borne diseases, particularly emphasizing the elevated likelihood of invasion by Southeast Asian mosquitoes.

METHODS

Field surveys were conducted in August 2023 on Jeju Island. Adult mosquitoes were collected using BG-sentinel traps and identified to the species level using taxonomic keys. Morphological and molecular analyses were employed to confirm species designations. Molecular data, including mitochondrial and nuclear genes, were used for phylogenetic analysis, which was performed to compare and identify among recorded subgenera in ROK. Species distribution modeling for Ae. laniger was performed to predict potential habitats using R package 'BIOMOD2'.

RESULTS

The two specimens of Ae. laniger were collected for the first time on Jeju Island. Morphological and molecular analyses confirmed the identity of this species within the subgenus Mucidus and validated the first record of this species in the ROK. We employed a simple multigene phylogenetic analysis to confirm a new mosquito record at the genus and subgenus levels, finally validating the consistency between morphological identification and molecular phylogenetic outcomes. Furthermore, we have updated the taxonomic keys for the genus Aedes in the ROK, and revised mosquito lists for Jeju Island, incorporating the inclusion of Ae. laniger. On the basis of species distribution modeling, the area of suitable habitat for Ae. laniger is expected to expand due to climate change, but this change did not appear to be meaningful in East Asia.

CONCLUSIONS

This case offers the first report of the Southeast Asian mosquito, Ae. laniger, in the ROK. The detection of this species on Jeju Island suggests the potential establishment of a breeding population their habitat and raises concerns about further expansion into the Korean Peninsula. Considering the annual occurrence of mosquito-borne disease cases in the Southeast Asia, it is essential to conduct monitoring not only in Jeju Island, where Ae. laniger has been identified, but also across the entire Korean Peninsula.

Spatiotemporal Characterization of Dengue Incidence and Its Correlation to Climate Parameters in Indonesia

Dengue has become a public health concern in Indonesia since it was first found in 1968. This study aims to determine dengue hotspot areas and analyze the spatiotemporal distribution of dengue and its association with dominant climate parameters nationally. Monthly data for dengue and climate observations (i.e., rainfall, relative humidity, average, maximum, and minimum temperature) at the regency/city level were utilized. Dengue hotspot areas were determined through K-means clustering, while Singular Value Decomposition (SVD) determined dominant climate parameters and their spatiotemporal distribution. Results revealed four clusters: Cluster 1 comprised cities with medium to high Incidence Rates (IR) and high Case Densities (CD) in a narrow area. Cluster 2 has a high IR and low CD, and clusters 3 and 4 featured medium and low IR and CD, respectively. SVD analysis indicated that relative humidity and rainfall were the most influential parameters on IR across all clusters. Temporal fluctuations in the first mode of IR and climate parameters were clearly delineated. The spatial distribution of heterogeneous correlation between the first mode of rainfall and relative humidity to IR exhibited higher values, which were predominantly observed in Java, Bali, Nusa Tenggara, the eastern part of Sumatra, the southern part of Kalimantan, and several locations in Sulawesi.

Low level of dengue infection and transmission risk in Hong Kong: an integrated analysis of temporal seroprevalence results and corresponding meteorological data

Hong Kong is an Asia-Pacific City with low incidence but periodic local outbreaks of dengue. A mixed-method assessment of the risk of expansion of dengue endemicity in such setting was conducted. Archived blood samples of healthy adult blood donors were tested for anti-dengue virus IgG at 2 time-points of 2014 and 2018/2019. Data on the monthly notified dengue cases, meteorological and vector (ovitrap index) variables were collected. The dengue virus (DENV) IgG seroprevalence of healthy adults in 2014 was 2.2% (95%C.I. = 1.8-2.8%, n = 3827) whereas that in 2018/2019 was 1.7% (95%C.I. = 1.2-2.3%, n = 2320). Serotyping on 42 sera in 2018/2019 showed that 22 (52.4%) were DENV-2. In 2002-2019, importation accounted for 95.3% of all reported cases. By wavelet analysis, local cases were in weak or no association with meteorological and vector variables. Without strong association between local cases and meteorological/vector variables, there was no evidence of increasing level of dengue infection in Hong Kong.

A methodology framework for bipartite network modeling

The graph-theoretic based studies employing bipartite network approach mostly focus on surveying the statistical properties of the structure and behavior of the network systems under the domain of complex network analysis. They aim to provide the big-picture-view insights of a networked system by looking into the dynamic interaction and relationship among the vertices. Nonetheless, incorporating the features of individual vertex and capturing the dynamic interaction of the heterogeneous local rules governing each of them in the studies is lacking. The methodology in achieving this could hardly be found. Consequently, this study intends to propose a methodology framework that considers the influence of heterogeneous features of each node to the overall network behavior in modeling real-world bipartite network system. The proposed framework consists of three main stages with principal processes detailed in each stage, and three libraries of techniques to guide the modeling activities. It is iterative and process-oriented in nature and allows future network expansion. Two case studies from the domain of communicable disease in epidemiology and habitat suitability in ecology employing this framework are also presented. The results obtained suggest that the methodology could serve as a generic framework in advancing the current state of the art of bipartite network approach.

The Threat of Climate Change on Tick-Borne Infections: Rising Trend of Infections and Geographic Distribution of Climate Risk Factors Associated With Ticks

Ticks transmit a wide range of pathogens. The spread of tick-borne infections is an emerging, yet often overlooked, threat in the context of climate change. The infections have rapidly increased over the past few years in South Korea despite no significant changes in socioeconomic circumstances. We investigated the impact of climate change on the surge of tick-borne infections and identified potential disease hot spots at a resolution of 5 km by 5 km. A composite index was constructed based on multiple climate and environmental indicators and compared with the observed tick-borne infections. The surge of tick-borne episodes corresponded to the rising trend of the index over time. High-risk areas identified by the index can be used to prioritize locations for disease prevention activities. Monitoring climate risk factors may provide an opportunity to predict the spread of the infections in advance.

Demographic and climatic factors associated with dengue prevalence in a hyperendemic zone in Mexico: an empirical approach

BACKGROUND

Many models for predicting dengue epidemics use incidence and short-term changes in climate variables, however, studies in real-life scenarios for correlations of seroprevalence (SP) with long-term climate variables and with integration of socio-economic factors are scarce. Our objective was to analyse the combined correlation between socio-economic and climate variables with the SP of dengue in Mexico.

METHODS

We performed a seroepidemiological ecological study on the Mexican Pacific coast. Dengue SP was estimated by the presence of immunoglobulin G antibodies in 1278 inhabitants. We implemented multiple correlations with socio-economic, climatic and topographic characteristics using logistic regression, generalized linear models and non-linear regressions.

RESULTS

Dengue SP was 58%. The age-adjusted correlation was positive with the male sex, while a negative correlation was seen with socio-economic status (SES) and scholl level (SL). The annual temperature showed a positive correlation, while the altitude was negative. It should be noted that these correlations showed a marked 'S' shape in the non-linear model, suggesting three clearly defined scenarios for dengue risk.

CONCLUSION

Low SES and SL showed an unexpected paradoxical protective effect. Altitude above sea level and annual temperature are the main determinants for dengue in the long term. The identification of three clearly delineated scenarios for transmission could improve the accuracy of predictive models.

A regional suitable conditions index to forecast the impact of climate change on dengue vectorial capacity

BACKGROUND

The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam).

METHODS

Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries.

FINDINGS

Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070.

INTERPRETATION

The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission.

Outbreaks of Vector-Borne and Zoonotic Diseases Are Associated With Changes in Forest Cover and Oil Palm Expansion at Global Scale

Deforestation is a major cause of biodiversity loss with a negative impact on human health. This study explores at global scale whether the loss and gain of forest cover and the rise of oil palm plantations can promote outbreaks of vector-borne and zoonotic diseases. Taking into account the human population growth, we find that the increases in outbreaks of zoonotic and vector-borne diseases from 1990 to 2016 are linked with deforestation, mostly in tropical countries, and with reforestation, mostly in temperate countries. We also find that outbreaks of vector-borne diseases are associated with the increase in areas of palm oil plantations. Our study gives new support for a link between global deforestation and outbreaks of zoonotic and vector-borne diseases as well as evidences that reforestation and plantations may also contribute to epidemics of infectious diseases. The results are discussed in light of the importance of forests for biodiversity, livelihoods and human health and the need to urgently build an international governance framework to ensure the preservation of forests and the ecosystem services they provide, including the regulation of diseases. We develop recommendations to scientists, public health officers and policymakers who should reconcile the need to preserve biodiversity while taking into account the health risks posed by lack or mismanagement of forests.

Sociodemographic predictors of knowledge, mosquito bite patterns and protective behaviors concerning vector borne disease: The case of dengue fever in Chinese subtropical city, Hong Kong

Geographic pattern of dengue fever is changing due to the global environmental and climate changes in the 21st century. Evidence of community's knowledge, mosquito bite patterns and protective behavior practices in non-endemic regions is limited. This study examined the knowledge of dengue, mosquito bite patterns, protective behavior practices and their associated factors in Hong Kong, a non-endemic subtropical city. A population-based random telephone survey (n = 590) was conducted three weeks after the government announcement of a local dengue outbreak in August 2018. Sociodemographic status, awareness, knowledge, protective measures, bite patterns of mosquito were collected. Results indicated high level of community awareness of the local outbreak (95.2%), symptom identification (84.0%) and adoption of at least one mosquito protective measures (nearly 80%). About 40% of respondents reported that they were bitten by mosquitoes during the study period, a high mosquito season in Hong Kong. Mosquito bites were prevalent near grassy area (63.4%), at home (42.6%) and at public transportation waiting spots (39.6%). Younger people (< 25 years old), female, those who lived on lower floors (≤the 6th) and near grassy area were at higher risk of mosquito bites at home. Respondents perceived higher threat of dengue to society were more likely to practice mosquito prevention. While residential factors affected their indoor prevention, other socio-demographic factors affected the outdoor prevention. Practicing prevention behaviors were associated with self-reported mosquito bite at home. Furthermore, the general prevention uptake rate unchanged after the announcement of local dengue outbreak. Although the uptake rate of protective measures during August was high, 40% participants reported they were bitten. Also public locations are more common area for bites, which suggested stronger mosquito prevention and control on public environments and more personal protective behaviors should be advocated.

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.

Retrospective cross-sectional observational study on the epidemiological profile of dengue cases in Pernambuco state, Brazil, between 2015 and 2017

BACKGROUND

The spread of Dengue virus (DENV) infections, as well as their signs and symptoms, are the result of a complex interaction between several factors. In Brazil, especially in the Northeastern, dengue is an important public health problem. Here, we report an epidemiological analysis of dengue cases in Pernambuco state, Northeastern Brazil, during 2015-2017.

METHODS

This work is a retrospective cross-sectional observational study on the epidemiological profile of all dengue cases confirmed and reported to the Health Secretary of Pernambuco between 2015 and 2017. These data cover all municipalities of Pernambuco, except Fernando de Noronha. DENV-positive individuals were classified according to the dengue type (without and with warning signs, or severe dengue), age, gender, ethnicity and intermediate geographic region of residence (Recife, Caruaru, Serra Talhada or Petrolina). The distribution of cases over the years was assessed by χ2 test. Temperature and rainfall data were evaluated by Unpaired t-test. p-value < 0.05 and CI 95% were considered in all analyses.

RESULTS

Most dengue cases was without warning signs. The most observed characteristics in the less severe dengue phenotypes were: female, mulatto ethnicity and age between 20 and 39 years old; this profile was more clearly observed in 2015. In 2016 and 2017, however, the numbers of dengue without and with warning signs were more evenly distributed and the difference in cases within groups decreased significantly. Regarding severe dengue, mulattoes were the most affected, but it is possible to note a trend towards a more uniform distribution between the genders and ages. Recife was the region with the highest numbers of both total cases and incidence rates and the highest rainfall levels. Overall, over the years, there has been a decrease in dengue cases in all regions of Pernambuco.

CONCLUSIONS

We identified the epidemiological profile of dengue in Pernambuco, Brazil, reporting the gender, age, ethnicity and regions most affected by different dengue types. In addition, we observed that these cases were probably more influenced by rainfall than by temperature. Finally, we believe that this epidemiological knowledge is important to direct public health policies to the reality of each population.

Epidemiological study on dengue in southern Brazil under the perspective of climate and poverty

Social and epidemiological aspects of dengue were evaluated in an important metropolitan area in southern Brazil, from August 2012 to September 2014. Demographic, clinical, serological data were collected from patients with acute dengue symptoms treated at public health system units (HSUs). A systematic approach to analyze the spatial and temporal distribution of cases was developed, considering the temporal cross-correlation between dengue and weather, and the spatial correlation between dengue and income over the city's census tracts. From the 878 patients with suggestive symptoms, 249 were diagnosed as positive dengue infection (28%). Considering the most statistically significant census tracts, a negative correlation was found between mean income and dengue (r = -0.65; p = 0.02; 95% CI: -0.03 to -0.91). The occurrence of dengue followed a seasonal distribution, and it was found to be three and four months delayed in relation to precipitation and temperature, respectively. Unexpectedly, the occurrence of symptomatic patients without dengue infection followed the same seasonal distribution, however its spatial distribution did not correlate with income. Through this methodology, we have found evidence that suggests a relation between dengue and poverty, which enriches the debate in the literature and sheds light on an extremely relevant socioeconomic and public health issue.

Spatial distribution of dengue in Honduras during 2016-2019 using a geographic information systems (GIS)-Dengue epidemic implications for public health and travel medicine

BACKGROUND

After serious epidemics of chikungunya (CHIKV) and Zika (ZIKV) in the Americas, dengue (DENV) have reemerged in most countries. We analyzed the incidence, incidence rates, and evolution of DENV cases in Honduras from 2015 to 2018 and the ongoing 2019 epidemic.

METHODS

Using epidemiological weeks (EW) surveillance data on the DENV in Honduras, we estimated incidence rates (cases/100,000 population), and developed maps at national, departmental, and municipal levels.

RESULTS

From January 1, 2016 to July 21, 2019, a total of 109,557 cases of DENV were reported, 28,603 in 2019, with an incidence rate of 312.32 cases/100,000 population this year; 0.13% laboratory-confirmed. The highest peak was reached on the EW 28°, 2019 (5299 cases; 57.89 cases/100,000 population). The department with the highest number of cases and incidence rate was Cortes (8404 cases, 479.68 cases/100,000 population in 2019).

DISCUSSION

The pattern and evolution of DENV epidemic in 2019 in Honduras has been similar to that which occurred for in 2015. As previously reported, this epidemic involved the north and central areas of the country predominantly, reaching municipality incidences there >1000 cases/100,000 population (or 1%). Studies using geographical information systems linked with clinical disease characteristics are necessary to obtain accurate epidemiological data for public health systems. Such information is also useful for assessment of risk for travelers who visit specific areas in a destination country.