Measures of Malaria Burden after Long-Lasting Insecticidal Net Distribution and Indoor Residual Spraying at Three Sites in Uganda: A Prospective Observational Study.
Measures of Malaria Burden after Long-Lasting Insecticidal Net Distribution and Indoor Residual Spraying at Three Sites in Uganda: A Prospective Observational Study.
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DOI：
10.1371/journal.pmed.1002167
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发表时间：
2016-11
期刊：
影响因子：
15.8
通讯作者：
Dorsey G
中科院分区：
文献类型：
--
作者：
Katureebe A;Zinszer K;Arinaitwe E;Rek J;Kakande E;Charland K;Kigozi R;Kilama M;Nankabirwa J;Yeka A;Mawejje H;Mpimbaza A;Katamba H;Donnelly MJ;Rosenthal PJ;Drakeley C;Lindsay SW;Staedke SG;Smith DL;Greenhouse B;Kamya MR;Dorsey G
长效杀虫蚊帐（LLINs）和室内杀虫剂残留喷洒（IRS）是非洲用于预防疟疾的主要媒介控制干预措施。尽管这两种干预措施在某些情况下是有效的，但在国家疟疾控制规划部署后，很少有高质量的证据来评估它们的有效性。在乌干达，我们测量了在三个地点普遍分布LLIN后主要疟疾指标的变化，并在其中一个地点增加了IRS。2011年10月1日至2016年3月31日，在三个传播相对较低（Walukuba）、中度（Kihihi）和高传播（Nagongera）的县开展了疟疾综合监测。2013年至2014年期间，在所有站点开展了普遍的LLIN分发活动，并于2014年12月在Nagongera启动了氨基甲酸酯灭虫威的IRS。高质量监测评估了干预前后的疟疾指标和蚊子暴露情况，方法是：(a)加强基于卫生设施的监测，以估计疟疾检测阳性率（TPR）表示为疟疾检测阳性的人数/疟疾检测人数（接受疟疾检测的儿童人数：Walukuba = 42,833人，Kihihi = 28,790人，Nagongera = 38,690人）；(b)估计疟疾发病率的队列研究，以每人每年有风险的疟疾发作次数表示（观察到的儿童人数：Walukuba = 340, Kihihi = 380, Nagongera = 361）；(c)昆虫学调查，估计住户水平的人类叮咬率（HBR），以每户-夜收集到的雌性按蚊数量表示（观察到的住户数量：Walukuba = 117, Kihihi = 107, Nagongera = 107）。LLIN分发活动大大提高了三个站点的LLIN覆盖率，至少拥有一个LLIN的家庭的覆盖率在65.0%至95.5%之间。在Walukuba,干预阶段28-mo,通用目标的分布与疟疾的发病率没有变化(0.39集0.20 PPY干预前与干预后;调整速度比(aRR) = 1.02, 95% CI 0.36 - -2.91, p = 0.97)和非重大的削减TPR(干预,干预前26.5%和26.2%,aRR = 0.70, 95% CI 0.46 - -1.06, p = 0.09)和哈佛商业评论(每0.71 house-night干预前与干预后1.07蚊子;aRR = 0.41, 95% CI 0.14-1.18, p = 0.10)。在Kihihi,干预阶段21-mo,通用目标的分布与减少疟疾的发病率(aRR干预,干预前1.77和1.89 = 0.65,95% CI 0.43 - -0.98, p = 0.04),但无显著的变化TPR(干预,干预前49.3%和45.9%,aRR = 0.83, 95% 0.58 - -1.18, p = 0.30)或哈佛商业评论(aRR干预,干预前4.06和2.44 = 0.71,95% CI 0.30 - -1.64, p = 0.40)。在Nagongera,干预阶段12-mo,通用目标的分布与减少TPR(干预,干预前45.3%和36.5%,aRR = 0.82, 95% CI 0.76 - -0.88, p < 0.001),但疟疾的发病率无显著变化(aRR干预,干预前2.82和3.28 = 1.10,95% 0.76 - -1.59,p = 0.60)或哈佛商业评论(aRR干预,干预前41.04和20.15 = 0.87,95% CI 0.31 - -2.47, p = 0.80)。在Nagongera每隔6个月增加三轮IRS后，所有结局均明显下降：疟疾发病率（干预前为3.25，干预后为0.63;aRR = 0.13, 95% CI 0.07-0.27, p < 0.001）、TPR（干预前为37.8%，干预后为15.0%;aRR = 0.54, 95% CI 0.49-0.60, p < 0.001）和HBR（干预前为18.71，干预后为3.23;aRR = 0.29, 95% CI 0.17-0.50, p < 0.001）。在所有三个研究地点都记录了高水平的拟除虫菊酯抗性。该研究的局限性包括观察性研究设计，缺乏同期对照组，以及干预措施是在程序化条件下实施的。在传播强度不同的3个地点普遍分布低剂量疟原虫与某些指标的疟疾负担略有下降有关，但在最高传播地点增加低剂量疟原虫与所有指标的疟疾负担显著下降有关。在非洲普遍存在拟除虫菊酯类杀虫剂耐药性的高流行地区，可能需要使用替代杀虫剂配方进行室内滞留，以在疟疾控制方面取得实质性成果。在这项前瞻性观察研究中，Grant Dorsey及其同事在乌干达的三个地点测量了长期分发杀虫剂蚊帐和室内残留喷洒后疟疾负担的变化。长效杀虫蚊帐（LLINs）可以防止蚊子在人睡觉时叮咬人，而室内残留喷洒杀虫剂（IRS）可以防止蚊子在室内休息，这是非洲预防疟疾的主要工具。尽管LLINs和IRS已被证明是有效的，但蚊子和人的行为变化以及对杀虫剂产生抗药性的蚊子的出现可能会损害这些干预措施的益处。最近，乌干达政府在全国范围内分发了免费的蚊帐，并在选定的地区开始了室内回收站。在这一“现实世界”环境中，重要的是监测在扩大LLIN分发和IRS后疟疾负担的变化。研究人员在2011年10月1日至2016年3月31日期间，在乌干达三个疟疾传播强度不同的地点进行了全面的疟疾监测。2013年至2014年期间，在所有三个站点向全体人口分发了杀虫剂，并于2014年12月在疟疾传播水平最高的站点开始使用与杀虫剂不同的杀虫剂进行IRS。这组科学家发现，在LLIN分布之后，这三个地点的疟疾负担的一些测量指标只有轻微下降，而其他测量指标没有变化。相比之下，在最高传播点增加IRS后，疟疾负担的所有测量值都急剧下降。该研究还记录了在所有三个地点对低龄杀虫剂使用的杀虫剂的高度抗性。这些发现表明，在像乌干达这样疟疾负担沉重的国家，单靠低剂量杀虫剂可能不足以大幅降低疟疾负担，可能需要使用不同的杀虫剂添加高剂量杀虫剂才能产生重大影响。但是，应当指出，IRS比分发llin更昂贵和更难执行，通常需要每6-12个月重复一次才能产生持续的效果。
Long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are the primary vector control interventions used to prevent malaria in Africa. Although both interventions are effective in some settings, high-quality evidence is rarely available to evaluate their effectiveness following deployment by a national malaria control program. In Uganda, we measured changes in key malaria indicators following universal LLIN distribution in three sites, with the addition of IRS at one of these sites. Comprehensive malaria surveillance was conducted from October 1, 2011, to March 31, 2016, in three sub-counties with relatively low (Walukuba), moderate (Kihihi), and high transmission (Nagongera). Between 2013 and 2014, universal LLIN distribution campaigns were conducted in all sites, and in December 2014, IRS with the carbamate bendiocarb was initiated in Nagongera. High-quality surveillance evaluated malaria metrics and mosquito exposure before and after interventions through (a) enhanced health-facility-based surveillance to estimate malaria test positivity rate (TPR), expressed as the number testing positive for malaria/number tested for malaria (number of children tested for malaria: Walukuba = 42,833, Kihihi = 28,790, and Nagongera = 38,690); (b) cohort studies to estimate the incidence of malaria, expressed as the number of episodes per person-year [PPY] at risk (number of children observed: Walukuba = 340, Kihihi = 380, and Nagongera = 361); and (c) entomology surveys to estimate household-level human biting rate (HBR), expressed as the number of female Anopheles mosquitoes collected per house-night of collection (number of households observed: Walukuba = 117, Kihihi = 107, and Nagongera = 107). The LLIN distribution campaign substantially increased LLIN coverage levels at the three sites to between 65.0% and 95.5% of households with at least one LLIN. In Walukuba, over the 28-mo post-intervention period, universal LLIN distribution was associated with no change in the incidence of malaria (0.39 episodes PPY pre-intervention versus 0.20 post-intervention; adjusted rate ratio [aRR] = 1.02, 95% CI 0.36–2.91, p = 0.97) and non-significant reductions in the TPR (26.5% pre-intervention versus 26.2% post-intervention; aRR = 0.70, 95% CI 0.46–1.06, p = 0.09) and HBR (1.07 mosquitoes per house-night pre-intervention versus 0.71 post-intervention; aRR = 0.41, 95% CI 0.14–1.18, p = 0.10). In Kihihi, over the 21-mo post-intervention period, universal LLIN distribution was associated with a reduction in the incidence of malaria (1.77 pre-intervention versus 1.89 post-intervention; aRR = 0.65, 95% CI 0.43–0.98, p = 0.04) but no significant change in the TPR (49.3% pre-intervention versus 45.9% post-intervention; aRR = 0.83, 95% 0.58–1.18, p = 0.30) or HBR (4.06 pre-intervention versus 2.44 post-intervention; aRR = 0.71, 95% CI 0.30–1.64, p = 0.40). In Nagongera, over the 12-mo post-intervention period, universal LLIN distribution was associated with a reduction in the TPR (45.3% pre-intervention versus 36.5% post-intervention; aRR = 0.82, 95% CI 0.76–0.88, p < 0.001) but no significant change in the incidence of malaria (2.82 pre-intervention versus 3.28 post-intervention; aRR = 1.10, 95% 0.76–1.59, p = 0.60) or HBR (41.04 pre-intervention versus 20.15 post-intervention; aRR = 0.87, 95% CI 0.31–2.47, p = 0.80). The addition of three rounds of IRS at ~6-mo intervals in Nagongera was followed by clear decreases in all outcomes: incidence of malaria (3.25 pre-intervention versus 0.63 post-intervention; aRR = 0.13, 95% CI 0.07–0.27, p < 0.001), TPR (37.8% pre-intervention versus 15.0% post-intervention; aRR = 0.54, 95% CI 0.49–0.60, p < 0.001), and HBR (18.71 pre-intervention versus 3.23 post-intervention; aRR = 0.29, 95% CI 0.17–0.50, p < 0.001). High levels of pyrethroid resistance were documented at all three study sites. Limitations of the study included the observational study design, the lack of contemporaneous control groups, and that the interventions were implemented under programmatic conditions. Universal distribution of LLINs at three sites with varying transmission intensity was associated with modest declines in the burden of malaria for some indicators, but the addition of IRS at the highest transmission site was associated with a marked decline in the burden of malaria for all indicators. In highly endemic areas of Africa with widespread pyrethroid resistance, IRS using alternative insecticide formulations may be needed to achieve substantial gains in malaria control. In this prospective observational study, Grant Dorsey and colleagues measure changes in malaria burden after long-lasting insecticidal net distribution and indoor residual spraying at three sites of in Uganda. Long-lasting insecticidal nets (LLINs), which prevent mosquitoes from biting people while they sleep, and indoor residual spraying of insecticides (IRS) in houses, which prevents mosquitoes from resting in houses, are the main tools used to prevent malaria in Africa. Although LLINs and IRS have been shown to be effective, changes in the behavior of mosquitoes and people as well as the emergence of mosquitoes resistant to insecticides could compromise the benefits of these interventions. Recently the government of Uganda distributed free LLINs throughout the country and began IRS in selected areas. In this “real world” setting, it is important to monitor for changes in the burden of malaria following the scale-up of LLIN distribution and IRS. The researchers conducted comprehensive malaria surveillance between October 1, 2011, and March 31, 2016, at three sites in Uganda that differed in the intensity of malaria transmission. Between 2013 and 2014, LLINs were distributed to the entire population at all three sites, and in December 2014, IRS with an insecticide different from that used in the LLINs was started in the site with the highest level of malaria transmission. The researchers found that following LLIN distribution, there were only modest declines in some measures of malaria burden at the three sites, and no changes in other measures. In contrast, following the addition of IRS at the highest transmission site, all measures of malaria burden declined dramatically. The research also documented a high level of resistance to the type of insecticide used in LLINS at all three sites. These findings suggest that in countries like Uganda, which has a heavy burden of malaria, LLINs alone may not be adequate to substantially drive down the burden of malaria, and the addition of IRS using a different insecticide may be needed to have a major impact. However, it should be noted that IRS is more expensive and harder to implement than distributing LLINs, and generally needs to be repeated every 6–12 months to have a sustained effect.
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DOI：
10.4269/ajtmh.2009.81.519
发表时间：
2009-09-01
影响因子：
3.3
作者：
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