Spatio-Temporal Patterns of Dengue Incidence in Medan City, North Sumatera, Indonesia

Historical Hot Spots of Dengue and Zika Viruses to Guide Targeted Vector Control in San Juan, Puerto Rico (2010-2022)

Dengue viruses (DENV) continue to cause large outbreaks in tropical countries, while chikungunya and Zika (ZIKV) viruses have added complexity to Aedes-borne disease prevention and control efforts. Because these viruses are transmitted by the same vectors in urban areas, it is useful to understand if sequential outbreaks caused by these viruses have commonalities, such as similar seasonal and spatial patterns, that would help anticipate and perhaps prevent future outbreaks. We explored and analyzed the heterogeneity of confirmed cases of DENV (2010-2014 and 2015-2022) and ZIKV (2016-2017) during outbreaks in the San Juan metropolitan area of Puerto Rico to explore their degree of overlap and prioritize areas for Aedes aegypti control. Deidentified, georeferenced case data were aggregated into grid cells (500 × 500 m) within a geographical information system of the study area and analyzed to calculate the degree of overlap between outbreaks. Spatial autocorrelations using local indicators of spatial associations were conducted to identify significant disease case hot spots and correlations between outbreaks. We found that 75% of cases during the three transmission periods were concentrated in 25% of the total number of grid cells covering the study area. We also found significant clustering of cases during each outbreak, enabling identification of consistent disease hot spots. Our results showed 85% spatial overlap between cases of ZIKV in 2015-2017 and DENV in 2010-2014 and 97% overlap between DENV cases in 2010-2014 and 2015-2022. These results reveal urban areas at greater risk of future arbovirus outbreaks that should be prioritized for vector control.

Unraveling the Variation Pattern of Oncomelania hupensis in the Yangtze River Economic Belt Based on Spatiotemporal Analysis

The construction of the Yangtze River Economic Belt (YEB) is a great national economic development strategy in China. As the YEB covers most endemic provinces of schistosomiasis japonica featured by low endemicity, this study aimed to investigate the spatiotemporal distribution pattern of Oncomelania hupensis (O. hupensis), which serves as the only intermediate host of Schistosoma japonicum in the YEB. Annual data reflecting the distribution of O. hupensis from 2015 to 2021 were collected from the National Institute of Parasitic Disease, Chinese Center for Disease Control and Prevention. Spatial autocorrelation analysis, hotspot analysis and space-time scan analysis were performed to explore the aggregation features and spatiotemporal dynamics of the snail distribution. The distribution of both total snail habitats (during 2015-2021) and emerging snail habitats (in 2016, 2018 and 2020) showed spatial autocorrelation (Z = 15.8~16.1, p < 0.05; Z = 2.3~7.5, p < 0.05). Hotspot (high-value areas in space) counties were mainly clustered in the alluvial plain of the middle and lower reaches of the YEB. Eight spatial and temporal clusters of snail habitats were scanned and were mainly concentrated in the counties of Anhui, Jiangxi, Hubei, Hunan and Jiangsu provinces along the Yangtze River. The YEB carries a tremendous burden of O. hupensis. Surveillance and risk identification based on the snail presence should be strengthened to provide reference for protecting humans and public health security in the YEB.

Efficacy Assessment of Autodissemination Using Pyriproxyfen-Treated Ovitraps in the Reduction of Dengue Incidence in Parañaque City, Philippines: A Spatial Analysis

Dengue is one of the most important vector-borne diseases worldwide and is a significant public health problem in the tropics. Mosquito control continues to be the primary approach to reducing the disease burden and spread of dengue virus (DENV). Aside from the traditional larviciding and adulticiding interventions, autodissemination using pyriproxyfen-treated (AD-PPF) ovitraps is one of the promising methods to complement existing vector control strategies. Our paper assessed the efficacy of AD-PPF in reducing DENV infections in two barangays in Parañaque City. Using saliva samples from the participants from both the control and intervention sites, we collected the seroprevalence data for three months in each of the two years. Spatial analysis was conducted to determine hotspot areas and identify DENV infection distributions across the trial periods. The results showed that the intervention site was identified as having a clustering of DENV infections in Month 0 of Year 1 and shifted to a random dispersion of dengue cases at the end of Month 3 in Year 2. The disappearance of the clustering of the intervention site translates to a decrease in the cases of DENV infection relative to the control site. Furthermore, we also identified that DENV transmission occurred at a small-scale level that did not go beyond 86 m. In conclusion, AD-PPF is suggested to be an effective strategy and may be used as an additional vector control approach, albeit based on this short-term implementation.

Dengue Transmission Mapping with Weather-Based Predictive Model in Three Southernmost Provinces of Thailand

This study aimed to show maps and analyses that display dengue cases and weather-related factors on dengue transmission in the three southernmost provinces of Thailand, namely Pattani, Yala, and Narathiwat provinces. Data on the number of dengue cases and weather variables including rainfall, rainy day, mean temperature, min temperature, max temperature, relative humidity, and air pressure for the period from January 2015 to December 2019 were obtained from the Bureau of Epidemiology, Ministry of Public Health and the Meteorological Department of Southern Thailand, respectively. Spearman rank correlation test was performed at lags from zero to two months and the predictive modeling used time series Poisson regression analysis. The distribution of dengue cases showed that in Pattani and Yala provinces the most dengue cases occurred in June. Narathiwat province had the most dengue cases occurring in August. The air pressure, relative humidity, rainfall, rainy day, and min temperature are the main predictors in Pattani province, while air pressure, rainy day, and max/mean temperature seem to play important roles in the number of dengue cases in Yala and Narathiwat provinces. The goodness-of-fit analyses reveal that the model fits the data reasonably well. The results provide scientific information for creating effective dengue control programs in the community, and the predictive model can support decision making in public health organizations and for management of the environmental risk area.