Hafeez Sidrah, Amin Muhammad, Munir Bilal Ahmed
Departement of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Al-Khwarizmi Institute of Computer Science (KICS), University of Engineering and Technology (UET), Lahore, Pakistan.
Al-Khwarizmi Institute of Computer Science (KICS), University of Engineering and Technology (UET), Lahore, Pakistan.
Spat Spatiotemporal Epidemiol. 2017 Jun;21:77-85. doi: 10.1016/j.sste.2017.04.001. Epub 2017 Apr 24.
Dengue is identified as serious vector born infectious disease by WHO, threating around 2.5 billion people around the globe. Pakistan is facing dengue epidemic since 1994 but 2010 and 2011 dengue outbreaks were worst. During 2011 dengue outbreak 22,562 cases were reported and 363 died due to this fatal infection in Pakistan. In this study, Lahore District was chosen as it was severely affected in 2011 dengue outbreak with 14,000 reported cases and 300 deaths. There is no vaccine developed yet for the disease control, so only effective early warning, prevention and control measures can reduce the potential disease risk.
This study proposes a method for detecting spatial autocorrelation of temporal dynamics of disease using Local Index of Spatial Autocorrelation (LISA) using three temporal indices: (a) how often the dengue cases occur, frequency index; (b) how long the epidemic wave prevails, duration index; (c) how significant dengue cases occur in successive periods, severity index. Overlay analysis of LISA value for each temporal index resulted in eight risk types.
The mapping of spatio-temporal risk indices and their overlay analysis identified that 10.6% area of Lahore (184.3km and population density 119,110persons/km) had high values for frequency, duration, and severity index (p<0.05) and 16% area (having 25% population) is at potential risk of dengue.
Spatial risk identification by using local spatial-autocorrelation helps in identifying other possible causes of disease risk and further strategic planning for prevention and control measures.
登革热被世界卫生组织认定为严重的病媒传播传染病，威胁着全球约25亿人口。自1994年以来，巴基斯坦一直面临登革热疫情，但2010年和2011年的登革热疫情最为严重。在2011年登革热疫情期间，巴基斯坦报告了22562例病例，363人死于这种致命感染。在本研究中，选择了拉合尔地区，因为该地区在2011年登革热疫情中受到严重影响，报告病例达14000例，死亡300人。目前尚未开发出用于疾病控制的疫苗，因此只有有效的早期预警、预防和控制措施才能降低潜在的疾病风险。
本研究提出了一种使用局部空间自相关指数（LISA）检测疾病时间动态空间自相关的方法，该方法使用三个时间指数：（a）登革热病例发生的频率，频率指数；（b）疫情波持续的时间，持续时间指数；（c）连续时期内登革热病例发生的显著性，严重程度指数。对每个时间指数的LISA值进行叠加分析，得出八种风险类型。
时空风险指数的映射及其叠加分析表明，拉合尔10.6%的地区（184.3平方公里，人口密度为每平方公里119110人）的频率、持续时间和严重程度指数较高（p<0.05），16%的地区（占人口的25%）存在登革热潜在风险。
使用局部空间自相关进行空间风险识别有助于识别疾病风险的其他可能原因，并为预防和控制措施进行进一步的战略规划。
