Modeling present and future climate risk of dengue outbreak, a case study in New Caledonia

Projection of dengue fever transmissibility under climate change in South and Southeast Asian countries

Vector-borne infectious disease such as dengue fever (DF) has spread rapidly due to more suitable living environments. Considering the limited studies investigating the disease spread under climate change in South and Southeast Asia, this study aimed to project the DF transmission potential in 30 locations across four South and Southeast Asian countries. In this study, weekly DF incidence data, daily mean temperature, and rainfall data in 30 locations in Singapore, Sri Lanka, Malaysia, and Thailand from 2012 to 2020 were collected. The effects of temperature and rainfall on the time-varying reproduction number (Rt) of DF transmission were examined using generalized additive models. Projections of location-specific Rt from 2030s to 2090s were determined using projected temperature and rainfall under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585), and the peak DF transmissibility and epidemic duration in the future were estimated. According to the results, the projected changes in the peak Rt and epidemic duration varied across locations, and the most significant change was observed under middle-to-high greenhouse gas emission scenarios. Under SSP585, the country-specific peak Rt was projected to decrease from 1.63 (95% confidence interval: 1.39-1.91), 2.60 (1.89-3.57), and 1.41 (1.22-1.64) in 2030s to 1.22 (0.98-1.51), 2.09 (1.26-3.47), and 1.37 (0.83-2.27) in 2090s in Singapore, Thailand, and Malaysia, respectively. Yet, the peak Rt in Sri Lanka changed slightly from 2030s to 2090s under SSP585. The epidemic duration in Singapore and Malaysia was projected to decline under SSP585. In conclusion, the change of peak DF transmission potential and disease outbreak duration would vary across locations, particularly under middle-to-high greenhouse gas emission scenarios. Interventions should be considered to slow down global warming as well as the potential increase in DF transmissibility in some locations of South and Southeast Asia.

Temperature and transmission of chikungunya, dengue, and Zika viruses: A systematic review of experimental studies on Aedes aegypti and Aedes albopictus

Mosquito-borne viruses are leading causes of morbidity and mortality in many parts of the world. In recent years, modelling studies have shown that climate change strongly influences vector-borne disease transmission, particularly rising temperatures. As a result, the risk of epidemics has increased, posing a significant public health risk. This review aims to summarize all published laboratory experimental studies carried out over the years to determine the impact of temperature on the transmission of arboviruses by the mosquito vector. Given their high public health importance, we focus on dengue, chikungunya, and Zika viruses, which are transmitted by the mosquitoes Aedes aegypti and Aedes albopictus. Following PRISMA guidelines, 34 papers were included in this systematic review. Most studies found that increasing temperatures result in higher rates of infection, dissemination, and transmission of these viruses in mosquitoes, although several studies had differing findings. Overall, the studies reviewed here suggest that rising temperatures due to climate change would alter the vector competence of mosquitoes to increase epidemic risk, but that some critical research gaps remain.

Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases

Vector-borne diseases (VBDs) pose a major threat to human and animal health, with more than 80% of the global population being at risk of acquiring at least one major VBD. Being profoundly affected by the ongoing climate change and anthropogenic disturbances, modelling approaches become an essential tool to assess and compare multiple scenarios (past, present and future), and further the geographic risk of transmission of VBDs. Ecological niche modelling (ENM) is rapidly becoming the gold-standard method for this task. The purpose of this overview is to provide an insight of the use of ENM to assess the geographic risk of transmission of VBDs. We have summarised some fundamental concepts and common approaches to ENM of VBDS, and then focused with a critical view on a number of crucial issues which are often disregarded when modelling the niches of VBDs. Furthermore, we have briefly presented what we consider the most relevant uses of ENM when dealing with VBDs. Niche modelling of VBDs is far from being simple, and there is still a long way to improve. Therefore, this overview is expected to be a useful benchmark for niche modelling of VBDs in future research.

Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia's most vulnerable Dengue outbreaks, with climate change, its location, and it's dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman's rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman's rho; r = -0.007, p > 0.05; r = 0.085, p > 0.05; and r = -0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is -666.50 [95% CI: -1711.86 to 378.86] and -953.05 [-2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles

Dengue hemorrhagic fever (DHF) is severe dengue with a hallmark of vascular leakage. β-tryptase has been found to promote vascular leakage in DHF patients, which could be a potential target for DHF treatment. This study aims to develop a theoretical background for designing and selecting human β-tryptase inhibitors through computational studies. Thirty-four α-keto-[1,2,3]-oxadiazoles scaffold-based compounds were used to generate 2D-QSAR models and for molecular docking studies with β-tryptase (PDB Code 4A6L). In addition, molecular dynamics (MD) simulation and molecular mechanics generalised born surface area (MM-GBSA) analysis on the binding of the reported most active compound, compound 11e, towards β-tryptase were performed. Finally, a structure-based pharmacophore model was generated. The selected 2D-QSAR models have statistically proven good models by internal and external validation as well as the y-randomization test. The docking results of compound 11e showed lower CDOCKER energy than the 4A6L co-crystallised ligand and a similar binding pattern as the 4A6L co-crystallised ligand. From molecular dynamics simulation, 4A6L in compound 11e bound state has RMSD below 2 Å throughout the 500 ns simulation, indicating the docked complex is stable. Besides, MM-GBSA analysis suggested the 4A6L-compound 11e docked complex (-66.04 Kcal/mol) is structurally as stable as the 4A6L-native ligand co-crystallized structure (-66.84 Kcal/mol). The best pharmacophore model identified features included hydrogen bond acceptor, ionic interaction, hydrophobic interaction, and aromatic ring, which contribute to the inhibitory potency of a compound. This study supplied insight and knowledge for developing novel chemical compounds with improved inhibition of β-tryptase.Communicated by Ramaswamy H. Sarma.

Arboviral disease outbreaks, Aedes mosquitoes, and vector control efforts in the Pacific

Recurring outbreaks of mosquito-borne diseases, like dengue, in the Pacific region represent a major biosecurity risk to neighboring continents through potential introductions of disease-causing pathogens. Aedes mosquitoes, highly prevalent in this region, are extremely invasive and the predominant vectors of multiple viruses including causing dengue, chikungunya, and Zika. Due to the absence of vaccines for most of these diseases, Aedes control remains a high priority for public health. Currently, international organizations put their efforts into improving mosquito surveillance programs in the Pacific region. Also, a novel biocontrol method using Wolbachia has been tried in the Pacific region to control Aedes mosquito populations. A comprehensive understanding of mosquito biology is needed to assess the risk that mosquitoes might be introduced to neighboring islands in the region and how this might impact arboviral virus transmission. As such, we present a comprehensive review of arboviral disease outbreak records as well as Aedes mosquito biology research findings relevant to the Pacific region collected from both non-scientific and scientific sources.

Optimal Validated Multi-Factorial Climate Change Risk Assessment for Adaptation Planning and Evaluation of Infectious Disease: A Case Study of Dengue Hemorrhagic Fever in Indonesia

(1) Background: This paper will present an elaboration of the risk assessment methodology by Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ), Eurac Research and United Nations University Institute for Environment and Human Security (UNU-EHS) for the assessment of dengue. (2) Methods: We validate the risk assessment model by best-fitting it with the number of dengue cases per province using the least-square fitting method. Seven out of thirty-four provinces in Indonesia were chosen (North Sumatra, Jakarta Capital, West Java, Central Java, East Java, Bali and East Kalimantan). (3) Results: A risk assessment based on the number of dengue cases showed an increased risk in 2010, 2015 and 2016 in which the effects of El Nino and La Nina extreme climates occurred. North Sumatra, Bali, and West Java were more influenced by the vulnerability component, in line with their risk analysis that tends to be lower than the other provinces in 2010, 2015 and 2016 when El Nino and La Nina occurred. (4) Conclusion: Based on data from the last ten years, in Jakarta Capital, Central Java, East Java and East Kalimantan, dengue risks were mainly influenced by the climatic hazard component while North Sumatra, Bali and West Java were more influenced by the vulnerability component.