| Background:Recent years, with the global warming, accelerated process of urbanization, rapiddevelopment of tourism and trade and the ecological environment changing, people raisedmore concern about the prevention and control of mosquito-borne diseases. Migration tothe Longgang district increased exponentially in the early1990s, and there were manyreports of outbreaks from mobile population. Currently, malaria has been under effectivecontrol in Longgang district, which is considered as a low-endemic area. Since Japaneseencephalitis and dengue fever emerged and the expansion of the scope of the ShenzhenSpecial Economic Zone exploded, Longgang District still faces the risk of outbreaks ofmalaria and other mosquito-borne infectious diseases. The occurrence of mosquito-bornediseases affects people’s health and economic construction of Longgang District. Greatchange of geographical environment in Longgang District has taken place, but therelationship between the environmental change in rapid urbanization process andmosquito-borne diseases remain unknown. In this study, we mainly discussed how themeteorological factors affect mosquito density and its distribution in Longgang District,and the environmental change in its rapid urbanization process was analyzed.Objective:1. To explore the use of geographic information system (GIS) and spatial analysis technique in mosquito-borne diseases research, this study analyzed the saptio-temporal characteristicsof malaria, dengue fever and Japanese encephalitis epidemic situation and theirenvironmental determinants in Longgang district since1990s.2. To understand mosquito population composition, density and seasonal fluctuation inLonggang District, and to analyze the relationship between adult mosquito density,landscape structure, and meteorological factors and to predict mosquito density distributionusing geographical information system and remotely sensed imagery, in order to providescientific evidence for vector control strategy.Methods:1. Mosquito-borne disease surveillance data and demographic data in Longgang Districtwere collected to establish a database to linke to the digital map. Descriptive analysis anddisease distribution mapping were conducted. Spatial autocorrelation analysis method andSpace-time scan statistics method were used to analyze the spatial distribution ofmosquito-borne diseases and to detect diseases cluster areas in Longgang district. Moranscatter plot, Space-time scan statistics and Monte Carlo method were conducted underGeoDa and SaTScan Spatial statistical package environment.2. Four years mosquito density surveillance data from10sub-districts and meteorologicaldata over the same surveillance period were collected. An SARIMA (SeasonalAutoregressive Integrated Moving Average) model was established to predict mosquitodensity and to analyze the relationship between mosquito density and meteorologicalfactors. Middle and eastern sub-districts were selected as survey fields for exploring howlandscape factors influencing mosquito density. Mosquito light traps and GIS datacollectors were used to capture mosquitos and mark accurate position information duringthe investigation period. Advanced Land Observing Satellite (ALOS) images were obtainedto extract landscape classification information to build a multiple regression model.Results:1. The temporal change of mosquito-borne diseases in Longgang district can be divided into three stages: a) High incidence stage (1993-1994). It was a continuation phase after themalaria outbreak of the Shenzhen City. b) Local epidemic stage (1995-2000). The incidenceof this stage was much lower than the previous one. c) Sporadic stage. After the year2001,mosquito-borne disease incidence rate maintained at a low level (monthly incidence lowerthan0.2/100000). Though it was indicated that there had been in a sporadic stage, inaddition to malaria cases, Japanese encephalitis and dengue fever emerged in this stage.2. The annual peak of mosquito-borne disease incidence begins at the end of spring and thebeginning of summer, and it lasts to the autumn. The climate of Longgang district is mildand humid, suitable for a variety of mosquito species breeding. Seasonal distribution ofmosquito-borne diseases basically coincides with the fluctuation pattern of disease vectorspopulation in Longgang district, indicating that vector plays an important inmosquito-borne diseases spreading.3. There was a significant positive spatial autocorrelation of mosquito-borne diseasesincidence for all10sub-districts. Two spatio-temporal clusters were detected by SaTScansoftware. Most likely cluster included Longgang, Pingdi, Pingshan, Kengzi sub-district.The cluster radius was9.84km, with an anuual incidence of187.2/100000, and relative riskwas30.46. Secondary cluster included Pinbghu and Buji sub-district. The cluster radius was4.76km, with an anuual incidence of100.1/100000, relative risk was17.83.4. One thousand six hundred and sixteen mosquito traps were set and25789mosquitoswere captured. All captured mosquitos could be classified into4genera and10species.Culex quinquefasciatus, the dominant mosquito species in Longgang district, accounted for84.86%(n=21884); Aedes albopictus accounted for8.99%(n=2318).5. The result of the SARIMA time series analysis showed that the average temperature,hours of sunshine and precipitation were the influential factors of mosquito densityfluctuation. SARIMA model can be uesd to predict mosquito density.6. Landscape structure was an influential factor of the distribution of adult mosquito densityin Longgang district. The center of Longgang sub-district and Longcheng sub-district werethe clusters of high mosquito density. Conclusion:Our study revealed that mosquito-borne diseases incidence in Longgang district is in asporadic trend. There are a variety of vector species in Longgang district. Theenvironmental structure of Longgang district is able to provide suitable climatic conditionsand various types of landscape habitat. Once an disease source imported, there would be anoutbreak in Longgang district. These results suggest that vector surveillance should bestrengthened. In this study, we not only explored the spatial distribution of adult mosquitodensity in Longgang district, bue also identified environmental factors including climateand landscape affecting adult mosquito density fluctuation in this region. These findingsmay help guiding the prevention and control practice. |
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