Journal of Vector Borne Diseases最新文献

Background objectives: Dengue outbreaks pose a significant public health threat in Raigarh City, Central India. During the 2023-2024 rainy season, there was a marked rise in febrile cases resembling dengue across urban areas. In response, ICMR-NIMR, in collaboration with local health authorities, initiated entomological surveillance campaign. This effort aimed to identify dengue vectors and implement rapid intervention strategies to mitigate disease transmission.

Methods: An entomological survey was conducted in 16 wards of the Raigarh city. The study incorporated epidemiological data spanning nine years (2016-2024), along with a detailed month-wise analysis of dengue cases reported in 2023 and 2024. Vector density was assessed with House Index (HI), Container Index (CI), and Breteau Index (BI), to identify high-risk areas and predominant vector species.

Results: A total of 2,080 water-holding containers were identified across 622 surveyed properties, for vector breeding. Among these, 67 (35%) were routinely used household containers, while 124 (65%) were disposable items. Larval collections yielded 986 Aedes specimens, including 104 pupae, with Aedes albopictus accounting for 85% of the total, followed by Aedes aegypti (8%) and Aedes vittatus (5%). The entomological indices reflected a critical vector proliferation scenario, with an HI of 17.35%, CI of 7%, and BI of 24.49.

Interpretation conclusion: Targeted entomological surveillance, community awareness programs with interventions have contributed to a notable reduction in dengue case incidence. The findings establish Aedes albopictus as the predominant dengue vector in the region, alongside Aedes aegypti.

Background objectives: Dengue fever, including its severe forms, remains a major public health concern in endemic regions. Early diagnosis is critical for effective disease management, yet current diagnostic methods vary in sensitivity and accessibility. This study aimed to evaluate the diagnostic performance of three commercially available NS1 ELISA kits against a chemiluminescence immunoassay (CLIA) reference standard.

Methods: A total of 321 archived serum samples, previously tested using the Dengue NS1 Autobio chemiluminescence immunoassay (CLIA), were further analyzed using three NS1 ELISA kits. Among these, 12 samples showed discordant results between at least one ELISA kit and the CLIA and were subsequently analyzed through RT-PCR-based dengue serotyping. The diagnostic performance of the ELISA kits, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall agreement, was assessed using MedCalc software. Agreement between tests was further evaluated using kappa (κ) statistics, and comparisons of κ values were conducted using Fleiss's Z-test.

Results: Among the 321 archived serum samples, 105 were initially identified as NS1-reactive and 216 as NS1-negative. RT-PCR confirmed three of the CLIA-positive results as false positives, adjusting the reference count to 102 NS1-reactive and 219 NS1-negative samples. Athenese-Dx ELISA demonstrated the highest sensitivity (98.04%) and agreement with reference (99.07%, κ = 0.978), followed by SD (Sensitivity = 95.10%, Agreement = 97.82%, κ = 0.949) and PanBio (Sensitivity = 94.12%, Agreement = 97.82%, κ = 0.949). Specificity remained high across all ELISA kits (99.07%-99.54%).

Interpretation conclusion: The evaluated ELISA kits demonstrated high specificity and strong agreement with the reference standard, with Athenese-Dx ELISA showing better diagnostic accuracy. NS1-based ELISA remains a valuable tool for dengue diagnosis, particularly in resource-limited settings. Further studies with serotype-specific analysis and larger sample sizes are warranted.

Malaria remains a critical public health challenge, disproportionately affecting sub-Saharan Africa. Although sub-Saharan Africa shoulders the greatest burden of malaria, research led by African institutions continues to receive only a small fraction of global research and development funding. This article reflects on the growing importance of South-South collaboration as a catalyst for advancing malaria research and control efforts. By drawing from initiatives like ANDI, the Elimination 8 (E8) group, and the India-Africa Health Sciences Platform, we illustrate how partnerships among low- and middle-income countries can foster innovation, strengthen local research capacity, improve diagnostic tools, enhance regional surveillance systems and address shared challenges. We also discuss barriers such as limited funding and fragmented systems, and outline strategies-like regional investment and regulatory harmonization-that could help unlock the full potential of these South-South collaborations.

Vector control programs have historically relied on chemical insecticides including organochlorines, organophosphates, carbamates, and pyrethroids but the rapid escalation of insecticide resistance in mosquito populations now threatens the sustainability of these interventions. While genetic and biochemical resistance mechanisms are well characterized, emerging evidence implicates the mosquito microbiome as an additional, underexplored factor influencing resistance. Several microbial taxa (Bacillus cereus, Enterobacter cloacae, Pseudomonas spp., Wolbachia) have been associated with detoxification pathways, yet causal links between these microbiota and specific resistance phenotypes remain weakly defined. Furthermore, the extent to which microbiome shifts modulate mosquito life-history traits such as survival, fecundity, and development time under sustained insecticide selection remains largely unknown. These traits are key determinants of vectorial capacity, and microbiome-mediated changes could alter disease transmission dynamics in ways not currently accounted for in control strategies. This review critically synthesizes evidence from 2005-2024, drawing on peer-reviewed studies, systematic reviews, and experimental work from NCBI, PubMed, ScienceDirect, and Google Scholar. We evaluate the interplay between insecticide-driven selection, microbiome composition, and mosquito biology, highlighting mechanistic uncertainties, methodological limitations, and gaps in longitudinal validation. The analysis underscores the urgent need for integrative research combining microbiome manipulation, functional genomics, and ecological monitoring to move from correlation to causation. By clarifying the microbiome-resistance nexus, this work aims to inform more sustainable, evidence-based strategies for long-term vector control.

Background objectives: Dengue has emerged as a major global public health threat, with a sharp rise in cases across endemic regions in recent decades. Bihar, a high-risk state in eastern India, has experienced its most severe dengue outbreaks recently, reporting 8,136 cases in 2019, 11,285 in 2022, and 19,093 in 2023. This study investigates the relationship between climate variability and dengue incidence across Bihar's 38 districts, including the capital city, Patna, over the period 2019-2023.

Methods: The analysis focuses on key meteorological factors-minimum, maximum, and mean temperatures, along with precipitation-and their time-lagged associations with weekly dengue case counts. Spatial patterns of dengue transmission are also assessed to identify regional hotspots.

Results: Results indicate that central Bihar exhibits the highest incidence of dengue during the study period. Among the examined variables, minimum temperature and rainfall show the strongest and most consistent correlations with dengue incidence, particularly with lags of 4 to 6 weeks.

Interpretation conclusion: These findings provide a foundation for developing climate-informed early warning systems and targeted vector control strategies, thereby enhancing preparedness and response to future dengue outbreaks in Bihar and similar regions.

The current systematic review and meta-analysis aims to estimate the prevalence of West Nile Virus (WNV) among humans in Iran. A comprehensive search was conducted in national databases, including SID, Magiran, and Barekat knowledge network and international databases, including Web of Science, MEDLINE, Embase, and Scopus, to identify the articles on the prevalence of human WNV in Iran. A random-effects model was used to assess the pooled prevalence. A meta-regression method was applied to determine the factors affecting the heterogeneity among the studied population. An analysis was performed on 11 studies with a total sample size of 3747. The total pooled estimate for the prevalence of human WNV was 14.92% (95% CI: 9.13 to 20.71). The highest pooled prevalence was in Khuzestan (southwest Iran) (58.31%; 95% CI: 21.12 to 90.82), and the lowest were in East Azerbaijan (Central Iran) (0.0%; 95% CI: 0.0 to 7.11) and Mazandaran (north Iran) (0.0%; 95% CI: 0.0 to 1.69), respectively. Based on the results of the univariate meta-regression, province (b: 0.35; p < 0.001) showed a significant direct association with the prevalence of human WNV, but other variables, including detection method, study population, publication year, and sample size, had no association with the prevalence of human WNV. The percentage of positive cases in serum samples shows that the WNV spreads in Iran.

Background objectives: Japanese Encephalitis (JE) is a re-emerging vector-borne zoonotic disease with a significant public health impact in India. JE is endemic in several Indian states, including Assam, which consistently reports the high burden of human JE cases in the country. Pigs, as amplifier hosts for the JE virus plays a critical role in JE transmission cycle and serves as suitable sentinels for predicting human JE outbreaks. Although several studies have assessed the JE prevalence in pigs across different districts of Assam, there is no prior report of occurrence of JE in pigs from Southern region of Assam. The present study was undertaken to determine the occurrence of JEV infection in pigs from Cachar, a Southern district of Assam through serological and molecular testing.

Methods: A total of 100 pig serum samples collected from backyard farms across eight villages in the Cachar district were screened using indirect ELISA(s) to detect JEV-specific IgM and IgG antibodies. Samples were further subjected to nested RT-PCR for viral RNA detection followed by phylogenetic analysis to identify the circulating JEV genotype in the region.

Results: Of the 100 pig serum samples tested, 59% were positive for JEV specific IgM antibodies whereas 53% samples were positive for IgG antibodies. The overall seropositivity of JEV among pigs from Cachar district was 66%. JEV RNA was detected in 12 samples and phylogenetic analysis confirmed the presence of genotype III of JEV circulating among pigs from Cachar district of Assam.

Interpretation conclusion: This is the first study to report the presence of JEV infection in pigs from the Cachar district of Assam, underscoring the need to initiate JEV surveillance in the pig population of the region.

Background objectives: The increasing prevalence of life-threatening viral diseases like dengue fever necessitates comprehensive research into their causes, recovery, and preventive measures. Dengue outbreak data often suffers from irregularities, underreporting, delays, and missing information, which challenge the development of reliable prediction models.

Methods: To overcome these issues, the study proposes an innovative framework that combines Evolutionary Sampling with Prediction (ESP) to handle temporal and stochastic dynamics, along with a Minimax K-nearest neighbour imputer to correct missing data biases. Additionally, a novel Firefly Dynamic Evolution (FDE) approach optimizes model parameters, while a Random Forest classifier captures complex, nonlinear relationships in the data. The model was evaluated using 10-fold cross-validation on two datasets: the Local Epidemics Dengue Fever dataset (San Juan and Iquitos) and the Brazil dengue dataset.

Results: The proposed model achieved a low Mean Absolute Error (MAE) of 22.1 and Root Mean Squared Error (RMSE) of 46.37 on the local dataset, and an MAE of 48.36 and RMSE of 86.76 on the Brazil dataset, demonstrating improved accuracy and robustness.

Interpretation conclusion: These findings highlight the model's potential for early warning systems and broader applications in forecasting other infectious diseases.

Background objectives: Rodents and arthropod vectors transmit zoonotic pathogens like Yersinia pestis, Rickettsia typhi etc. posing a threat to both veterinary and public health. The primary aim of this study was to record the incidence of rat fleas, a vector for plague and murine typhus on synanthropic rodents, their epidemiology and molecular characterization.

Methods: A comprehensive survey of synanthropic rodents viz. Bandicota bengalensis (190), Rattus rattus (201), and Tatera indica (180) across various habitats, including crop fields, poultry farms, fish markets, residential areas, shops, and railway stations in different seasons, was conducted to record the incidence of rat fleas. Fleas collected were identified morphologically, followed by molecular confirmation through PCR amplification of 28S rRNA gene and phylogenetic analysis.

Results: Morphological and molecular analyses confirmed the flea species as Xenopsylla cheopis. The nucleotide sequence obtained was submitted to GenBank (LC626773). The infestation rate varied among rodent species, with R. rattus exhibiting the highest prevalence (55.72%), followed by B. bengalensis (37.36%) and T. indica (6.67%). Adult male rodents were more frequently infested. Seasonal variations revealed peak infestations during winter (36.41%), particularly among rodents from poultry farms (63.33%). R. rattus posed the highest risk for disease transmission (8.35), followed by B. bengalensis (5.60).

Interpretation conclusion: This study highlights the critical role of R. rattus and B. bengalensis in spreading pathogens as primary hosts for X. cheopis. These findings emphasize the need for integrated vector surveillance and targeted control measures to reduce the risk of flea-borne zoonoses in urban and peri-urban areas.

Background objectives: In 2021, a Yellow Fever (YF) outbreak occurred in rural and mostly nomadic communities within the Savannah region of Ghana, leading to over 40 deaths. Following this outbreak, we determined the knowledge, attitude, and practice (KAP) of YF in these hotspot communities.

Methods: A cross-sectional study was conducted using a random sampling technique and a standard questionnaire involving face-to-face interviews from June 2022 to July 2022. Four districts were selected among the hotspot areas of the 2021 YF outbreak. The participants targeted were residents aged 15 years and above.

Results: The majority (80.8%) had heard about YF through healthcare personnel in all four districts. Most of them associated the cause with poor sanitation, but 14% specifically associated it with mosquito bites (N=869). The level of education was associated with awareness of YF (P = 0.008), however, a pairwise analysis did not show any association between those with no formal education and the highest education (P = 0.903). Vaccination rates were high (average 78%), and the distance to health facility influenced the vaccination status (P < 0.0001). Preventive measures employed included vaccination, sleeping under insecticide-treated bed nets, clearing bushes and getting rid of stagnant water.

Interpretation conclusion: There was high awareness of YF and vaccination rates among the participants. The emergency mass YF vaccination conducted in 2021 in response to the outbreak increased community awareness. Preventive practices employed may be associated with participants' knowledge of mosquito-borne diseases such as malaria. YF education should be integrated with routine health service delivery.