Exploring 30 years of malaria case data in KwaZulu-Natal, South Africa: Part I. The impact of climatic factors
Exploring 30 years of malaria case data in KwaZulu-Natal, South Africa: Part I. The impact of climatic factors
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DOI：
10.1111/j.1365-3156.2004.01340.x
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发表时间：
2004-12-01
影响因子：
3.3
通讯作者：
Sharp, BL
中科院分区：
文献类型：
--
作者：
Craig, MH;Kleinschmidt, I;Sharp, BL
非洲大部分地区容易发生疟疾流行。提前流行病预警将为卫生服务提供做好准备的机会。由于疟疾传播在很大程度上受到气候的限制，因此基于气候的流行病预警系统确实有可能实现。为了开发和测试这样的系统，需要良好的长期疟疾和气候数据。在南非夸祖鲁-纳塔尔省 (KZN)，30 年的疟疾确诊病例数据为研究短期和长期趋势提供了独特的机会。我们使用线性回归分析，根据从疟疾发病率最高地区的三个气象站获得的一系列气候指标，分析了季节性病例总数和病例季节性变化（均为对数转换）。病例数的季节性变化（δ对数病例，dlc）与多种气候变量显着相关。最重要的两个是前一季节 1 月至 10 月的平均最高日气温（n = 30，r(2) = 0.364，P = 0.0004）和当前夏季 11 月至 3 月的总降雨量（n = 30，r(2) = 0.282，P = 0.003）。当将这两个变量输入同一回归模型时，它们共同解释了 dlc 总变异的 49.7%。我们没有发现病例总数与气候之间存在关联的证据。在疟疾控制行动十分密集的夸大省，气候似乎会推动疟疾发病率的年际变化，但不会影响其总体水平。随附的论文提供的证据表明，总体水平与非气候因素有关，例如耐药性和可能的艾滋病毒流行率。
Large parts of Africa are prone to malaria epidemics. Advance epidemic warning would give health services an opportunity to prepare. Because malaria transmission is largely limited by climate, climate-based epidemic warning systems are a real possibility. To develop and test such a system, good long-term malaria and climate data are needed. In KwaZulu-Natal (KZN), South Africa, 30 years of confirmed malaria case data provide a unique opportunity to examine short- and long-term trends. We analysed seasonal case totals and seasonal changes in cases (both log-transformed) against a range of climatic indicators obtained from three weather stations in the highest malaria incidence districts, using linear regression analysis. Seasonal changes in case numbers (delta log cases, dlc) were significantly associated with several climate variables. The two most significant ones were mean maximum daily temperatures from January to October of the preceding season (n = 30, r(2) = 0.364, P = 0.0004) and total rainfall during the current summer months of November-March (n = 30, r(2) = 0.282, P = 0.003). These two variables, when entered into the same regression model, together explained 49.7% of the total variation in dlc. We found no evidence of association between case totals and climate. In KZN, where malaria control operations are intense, climate appears to drive the interannual variation of malaria incidence, but not its overall level. The accompanying paper provides evidence that overall levels are associated with non-climatic factors such as drug resistance and possibly HIV prevalence.