| Malaria, a natural local infectious disease caused by plasmodium and transmitted via mosquitoes, still poses a threat to 3.2 billion people in 97 countries and regions at present. Malaria has a long history and has always been considered as one of the important public health problems in China. The incidence of malaria has always ranked top two since 2000 in Hainan province, and relevant reported cases in 2004 accounted for 24.4% of the total cases in China, constituting the reason why it is viewed as the key area of malaria prevention. Despite a good malaria control in Hainan due to the great achievements in national malaria prevention and control strategy in recent years, surveillance and preventive measures cannot be ignored because of the possibility of outbreak resulting from its fast transmission and easy recurrence.Hainan is of economic and military importance. Using national epidemic surveillance data, national meteorological monitoring information, geographic information system(GIS) and remote sensing satellite maps, our research group carries out a study on the distribution characteristics, influencing factors as well as simulation and prediction of malaria in this region by virtue of large surveillance data and geographical feature information with detailed classification. This study aims at demonstrating the effectiveness of these comprehensive technical analyses, which facilitates the introduction of spatial epidemiology technologies into field epidemiological investigation of malaria and sanitary epidemiological reconnaissance in the army of this region.Methods1. The malaria epidemic surveillance data from 1993 to 2012 in Hainan province were collected from Hainan Disease Control Center and China Disease Prevention and Control Information System. Descriptive epidemiological method was used to analyze the temporal, regional and population distribution characteristics of malaria in Hainan. The spatial distribution characteristics of malaria between 2004 and 2012 in Hainan were displayed with Arc GIS drawings.2. The remote sensing data products from 2004 to 2008 in Hainan were obtained from NASA LAADS web site and SRTM. HEG software was used for data splicing, conversion and projection, while Arc GIS software was used to get land use/cover type ratio, elevation, NDVI, LSTD and LSTN data and make corresponding thematic maps. The corresponding meteorological data, including monthly rainfall, average wind speed, average temperature, average lowest and highest temperatures, average relative humidity as well as percentage and hours of sunshine were obtained from China Meteorological Data Sharing Service System before the descriptive analysis was conducted.3. Spearman rank correlation analysis, logisitic regression model and panel data model were applied to analyze the relation of incidence with environmental factors, influence of land use/cover type and altitude on malaria, influence of meteorological factors as well as environmental factors like NDVI, LSTD and LSTN on malaria, respectively.4. The logistic regression equation was verified by using the land use/cover type ratios and altitudes from 2004 to 2008 in various cities and counties. The malaria intensity in these regions was judged by the equation.Results:1. The malaria composition in Hainan province between 1993 and 2012 was dominated by vivax malaria, accounting for 60%, with falciparum malaria accounting for 19% and unclassified malaria accounting for 21%. There were three peak periods of malaria incidence: 110.40/100,000 in 1994, 71.45/100,000 in 1998 and 112.9/100,000 in 2004. The incidence tended to declined and showed remarkable seasonality from 2004 to 2008. The incidence peaks were from May to October. With the successful implementation of the NSA, the incidence of malaria after 2008 was rapidly decreased and showed no significant seasonal variation.2. The male and female prevalence ratio of malaria was 2.6:1 in Hainan between 2004 and 2008, and most of them were 30 to 59 years old, accounting for 55.04%. Peasants and rural migrant workers were the major occupational populations of malaria incidence, accounting for 36% and 35% of the total case report.3. The quantitative information of the geological characteristics of 2 types(land cover type and land use type) and 15 subclasses(forest land, crop, city, etc.) were extracted from the satellite map through GIS system. The correlation analysis showed that those factors having positive correlations with malaria incidence included evergreen broad-leaf forest, deciduous coniferous forest, deciduous broad-leaf forest, mingled forest, enclosed brush and altitude; while those factors having negative correlations with malaria included water, evergreen coniferous forest, woody savanna, savanna, grassland, permanent wetland, crop, city and built-up area; precipitation, sunlight, air temperature, NDVI and their lagged values one month later were positively correlated with malaria incidence; LSTD, LSTN and their lagged values one month later were negatively correlated with malaria incidence.4. Geological information was extracted using GIS system to analyze the geological spatial distribution characteristics from 2004 to 2008. The result indicated that malaria incidence showed an obvious regional distribution of high-incidence in the southwest and low-incidence in the northwest. The southwest(Baisha, Changjiang, Ledong, Linshui, Baoting, Qiongzhong, Wuzhishan, Dongfang and Wangning) had the geographical landscape characteristic mainly presented by forest land coverage; while the northwest(Haikou, Wenchang, High velocity, Cheng Mai, Anding, Danzhou, Tun Chang and Qionghai) mainly presented by grassland and crop coverage. The result of the multivariate analysis showed that evergreen broad-leaf forest(mean altitude: 734m) was the risk factor of malaria incidence, while coniferous forest zone(mean altitude: 63m) and crop zone(mean altitude: 263m) were the protective factors of malaria incidence.5. The multivariate panel data analysis showed that the increase of malaria incidence in Hainan was associated with the increase of NDVI index, the decrease of LSTD and the increase of sunshine duration: every unit increase in NDVI index, IRR=5.15(95% CI: 3.04-8.70); every 1℃ increase in LSTD, IRR=0.87(95% CI: 0.85-0.89); every 1℃ increase in LSTD one month ago, IRR=0.89(95%CI: 0.87-0.91); every 1 hour in sunshine duration, IRR=1.03(95% CI: 1.03-1.04); p=0.00.6. The malaria intensity in Hainan was verified by the logistic regression equation as follow:Altitude "0.06*"- Crop "*" 0.91 leaf "--broad Evergreen" *0.50 + forest " coniferous Evergreen" *12.59-11.48=logit(p)The final coincidence rate of the intensity discrimination results in various cities and counties from 2004 to 2008 was 87.77%.Conclusions:1. The prevention and control of malaria in Hainan achieves remarkable effects, but there still exist favorable environmental conditions for malaria transmission. Therefore, it is necessary to further strengthen the prevention and control of malaria.2. The long-term surveillance data of malaria epidemic situation indicate that the distribution of malaria has obvious regional(high-incidence in the southwest and low-incidence in the northwest) and periodic(high-incidence in summer and autumn and low-incidence in spring and winter) features. Young and middle male peasants and rural migrant workers were the high-risk population of malaria. We should take measures for the above-mentioned population according to their distribution characteristics.3. NDVI index, land surface temperature and sunshine duration are important environmental factors affecting malaria incidence, and their change rules can provide clues for the variations of malaria monitoring.4. GIS-based spatial epidemiological technology can extract the geological characteristics information of Hainan province in a rapid and accurate way. Vegetation form, land cover and use type are associated with disease intensity, so they can be used as important evidences for predicting malaria epidemic situation with the effect of natural factors. |
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