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      Quantifying Seasonal Variation in Insecticide-Treated Net Use among Those with Access

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          Abstract.

          Seasonal variation in the proportion of the population using an insecticide-treated net (ITN) is well documented and is widely believed to be dependent on mosquito abundance and heat, driven by rainfall and temperature. However, seasonal variation in ITN use has not been quantified controlling for ITN access. Demographic and Health Survey and Malaria Indicator Survey datasets, their georeferenced data, and public rainfall and climate layers were pooled for 21 countries. Nine rainfall typologies were developed from rainfall patterns in Köppen climate zones. For each typology, the odds of ITN use among individuals with access to an ITN within their households (“ITN use given access”) were estimated for each month of the year, controlling for region, wealth quintile, residence, year, temperature, and malaria parasitemia level. Seasonality of ITN use given access was observed over all nine rainfall typologies and was most pronounced in arid climates and less pronounced where rainfall was relatively constant throughout the year. Peak ITN use occurred 1–3 months after peak rainfall and corresponded with peak malaria incidence and average malaria transmission season. The observed lags between peak rainfall and peak ITN use given access suggest that net use is triggered by mosquito density. In equatorial areas, ITN use is likely to be high year-round, given the presence of mosquitoes and an associated year-round perceived malaria risk. These results can be used to inform behavior change interventions to improve ITN use in specific times of the year and to inform geospatial models of the impact of ITNs on transmission.

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          Most cited references61

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          A climate-based distribution model of malaria transmission in sub-Saharan Africa.

          Malaria remains the single largest threat to child survival in sub-Saharan Africa and warrants long-term investment for control. Previous malaria distribution maps have been vague and arbitrary. Marlies Craig, Bob Snow and David le Sueur here describe a simple numerical approach to defining distribution of malaria transmission, based upon biological constraints of climate on parasite and vector development. The model compared well with contemporary field data and historical 'expert opinion' maps, excepting small-scale ecological anomalies. The model provides a numerical basis for further refinement and prediction of the impact of climate change on transmission. Together with population, morbidity and mortality data, the model provides a fundamental tool for strategic control of malaria.
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            A global index representing the stability of malaria transmission.

            To relate stability of malaria transmission to biologic characteristics of vector mosquitoes throughout the world, we derived an index representing the contribution of regionally dominant vector mosquitoes to the force of transmission. This construct incorporated published estimates describing the proportion of blood meals taken from human hosts, daily survival of the vector, and duration of the transmission season and of extrinsic incubation. The result of the calculation was displayed globally on a 0.5 degrees grid. We found that these biologic characteristics of diverse vector mosquitoes interact with climate to explain much of the regional variation in the intensity of transmission. Due to the superior capacity of many tropical mosquitoes as vectors of malaria, particularly those in sub-Saharan Africa, antimalaria interventions conducted in the tropics face greater challenges than were faced by formerly endemic nations in more temperate climes.
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              The evidence for improving housing to reduce malaria: a systematic review and meta-analysis

              Background The global malaria burden has fallen since 2000, sometimes before large-scale vector control programmes were initiated. While long-lasting insecticide-treated nets and indoor residual spraying are highly effective interventions, this study tests the hypothesis that improved housing can reduce malaria by decreasing house entry by malaria mosquitoes. Methods A systematic review and meta-analysis was conducted to assess whether modern housing is associated with a lower risk of malaria than traditional housing, across all age groups and malaria-endemic settings. Six electronic databases were searched to identify intervention and observational studies published from 1 January, 1900 to 13 December, 2013, measuring the association between house design and malaria. The primary outcome measures were parasite prevalence and incidence of clinical malaria. Crude and adjusted effects were combined in fixed- and random-effects meta-analyses, with sub-group analyses for: overall house type (traditional versus modern housing); screening; main wall, roof and floor materials; eave type; ceilings and elevation. Results Of 15,526 studies screened, 90 were included in a qualitative synthesis and 53 reported epidemiological outcomes, included in a meta-analysis. Of these, 39 (74 %) showed trends towards a lower risk of epidemiological outcomes associated with improved house features. Of studies assessing the relationship between modern housing and malaria infection (n = 11) and clinical malaria (n = 5), all were observational, with very low to low quality evidence. Residents of modern houses had 47 % lower odds of malaria infection compared to traditional houses (adjusted odds ratio (OR) 0°53, 95 % confidence intervals (CI) 0°42–0°67, p < 0°001, five studies) and a 45–65 % lower odds of clinical malaria (case–control studies: adjusted OR 0°35, 95 % CI 0°20–0°62, p <0°001, one study; cohort studies: adjusted rate ratio 0°55, 95 % CI 0°36–0°84, p = 0°005, three studies). Evidence of a high risk of bias was found within studies. Conclusions Despite low quality evidence, the direction and consistency of effects indicate that housing is an important risk factor for malaria. Future research should evaluate the protective effect of specific house features and incremental housing improvements associated with socio-economic development. Electronic supplementary material The online version of this article (doi:10.1186/s12936-015-0724-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Am J Trop Med Hyg
                Am. J. Trop. Med. Hyg
                tpmd
                tropmed
                The American Journal of Tropical Medicine and Hygiene
                The American Society of Tropical Medicine and Hygiene
                0002-9637
                1476-1645
                August 2019
                01 July 2019
                01 July 2019
                : 101
                : 2
                : 371-382
                Affiliations
                [1 ]PMI VectorWorks Project, Johns Hopkins Bloomberg School of Public Health Center for Communication Programs, Baltimore, Maryland;
                [2 ]The Demographic and Health Surveys (DHS) Program, ICF, Rockville, Maryland;
                [3 ]RTI International, Washington, District of Columbia;
                [4 ]Malaria Branch, Centers for Disease Control and Prevention, Atlanta, Georgia;
                [5 ]PMI VectorWorks Project, Tropical Health LLP, Montagut, Spain
                Author notes
                [* ]Address correspondence to Hannah Koenker, 111 Market Place Suite 310, Baltimore, MD 21202. E-mail: hkoenker@ 123456jhu.edu

                Financial support: This work was made possible by the generous support of American people through the United States Agency for International Development (USAID) and the President’s Malaria Initiative (PMI) under the terms of USAID/JHU Cooperative Agreement No. AID-OAA-A-14-00057 (VectorWorks Project). The contents are the responsibility of the authors and do not necessarily reflect the views of USAID or the United States government.

                Authors’ addresses: Hannah Koenker, PMI VectorWorks, Johns Hopkins Center for Communication Programs, Baltimore, MD, E-mail: hkoenker@ 123456jhu.edu . Cameron Taylor and Tom Fish, The DHS Program, ICF, Rockville, MD, E-mails: cameron.taylor@ 123456icf.com and tom.fish@ 123456icf.com . Clara R. Burgert-Brucker, RTI International, Washington, DC, E-mail: cburgert@ 123456rti.org . Julie Thwing, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, GA, E-mail: fez3@ 123456cdc.gov . Albert Kilian, PMI VectorWorks Project, Tropical Health LLP, Montagut, Spain, E-mail: albert@ 123456trophealth.com .

                Article
                tpmd190249
                10.4269/ajtmh.19-0249
                6685578
                31264562
                0580051f-6bc2-4802-962a-4dbe7a8670cd
                © The American Society of Tropical Medicine and Hygiene

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 01 April 2019
                : 25 May 2019
                Page count
                Pages: 12
                Categories
                Articles

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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