AN EARLY WARNING SYSTEM FOR MALARIA IN MOPANI DISTRICT: DIVERGENT OR CONVERGENT APPROACHES

B. B.N. Rumutsa, N. Nethengwe
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Abstract

Abstract. Malaria is a tropical climate-change concatenated biological hazard that may, like any other hazard, lead to a disaster and requires a multidisciplinary divergent approach. This research was carried out in Mopani District of South Africa. It sought find out whether the existing early warning system in Mopani District is adopting a convergent or divergent approach. Subsequently, this was to assist in developing a tool that covers the loopholes in the existing system to further mitigate malaria transmissions. The study took a mixed approach. Data was collected from 381 selected participants through in-depth interviews, a survey, and a focus group discussion. Multiple sampling techniques were used in this study. In-depth interviews respondents were selected through snowballing, questionnaire survey respondents were sampled randomly, while for the discussants in the focus group discussion were purposively sampled. The study applied constructivist grounded theory to analyse qualitative data and to generate theory. Results of the study show that people in Mopani District predict the malaria season onset by forecasting rainfall using various indigenous knowledge-based indicators. The rainfall indicators mentioned by participants in the study were used to develop an early warning system. In the design of the system, Apache Cordova, JDK 1.8, Node JS, and XAMPP software were used. The study recommends malaria management and control key stakeholders to adopt the developed early warning system to further mitigate malaria transmission in Mopani District.
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莫帕尼地区疟疾早期预警系统:发散或趋同方法
摘要疟疾是一种与热带气候变化相关的生物危害,与任何其他危害一样,可能导致灾难,需要多学科的发散性方法。这项研究是在南非莫帕尼区进行的。它试图查明莫帕尼地区现有的预警系统是采用趋同的还是发散的办法。随后,这是为了协助开发一种工具,以弥补现有系统中的漏洞,进一步减轻疟疾传播。这项研究采用了一种混合的方法。通过深度访谈、调查和焦点小组讨论,从381名选定的参与者中收集数据。本研究采用了多种抽样技术。深度访谈的受访者采用滚雪球法进行抽样,问卷调查的受访者采用随机抽样,而对于焦点小组讨论中的讨论者采用有目的抽样。本研究运用建构主义扎根理论对定性数据进行分析并生成理论。研究结果表明,莫帕尼区的人们通过使用各种基于土著知识的指标预测降雨量来预测疟疾季节的到来。研究参与者提到的降雨指标被用于开发早期预警系统。在系统的设计中,使用了Apache Cordova、JDK 1.8、Node JS和XAMPP软件。该研究建议疟疾管理和控制的主要利益攸关方采用已开发的早期预警系统,以进一步减轻莫帕尼地区的疟疾传播。
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