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Yu Q, Qu Y, Zhang L, Yao X, Yang J, Chen S, Liu H, Wang Q, Wu M, Tao J, Zhou C, Alage IL, Liu S. Spatial spillovers of violent conflict amplify the impacts of climate variability on malaria risk in sub-Saharan Africa. Proc Natl Acad Sci U S A 2024; 121:e2309087121. [PMID: 38557184 PMCID: PMC11009658 DOI: 10.1073/pnas.2309087121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 02/02/2024] [Indexed: 04/04/2024] Open
Abstract
Africa carries a disproportionately high share of the global malaria burden, accounting for 94% of malaria cases and deaths worldwide in 2019. It is also a politically unstable region and the most vulnerable continent to climate change in recent decades. Knowledge about the modifying impacts of violent conflict on climate-malaria relationships remains limited. Here, we quantify the associations between violent conflict, climate variability, and malaria risk in sub-Saharan Africa using health surveys from 128,326 individuals, historical climate data, and 17,429 recorded violent conflicts from 2006 to 2017. We observe that spatial spillovers of violent conflict (SSVCs) have spatially distant effects on malaria risk. Malaria risk induced by SSVCs within 50 to 100 km from the households gradually increases from 0.1% (not significant, P>0.05) to 6.5% (95% CI: 0 to 13.0%). SSVCs significantly promote malaria risk within the average 20.1 to 26.9 °C range. At the 12-mo mean temperature of 22.5 °C, conflict deaths have the largest impact on malaria risk, with an approximately 5.8% increase (95% CI: 1.0 to 11.0%). Additionally, a pronounced association between SSVCs and malaria risk exists in the regions with 9.2 wet days per month. The results reveal that SSVCs increase population exposure to harsh environments, amplifying the effect of warm temperature and persistent precipitation on malaria transmission. Violent conflict therefore poses a substantial barrier to mosquito control and malaria elimination efforts in sub-Saharan Africa. Our findings support effective targeting of treatment programs and vector control activities in conflict-affected regions with a high malaria risk.
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Affiliation(s)
- Qiwei Yu
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Ying Qu
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Liqiang Zhang
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Xin Yao
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Jing Yang
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Siyuan Chen
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Hui Liu
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Qihao Wang
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Mengfan Wu
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Junpei Tao
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
| | - Chenghu Zhou
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing100101, China
| | - Isiaka Lukman Alage
- Space Research and Development Division, African Regional Centre for Space Science and Technology Education in English Ile ife, Ile ife, Osun220282, Nigeria
| | - Suhong Liu
- Department of Geography, State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing100875, China
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Ferriss E, Chaponda M, Muleba M, Kabuya JB, Lupiya JS, Riley C, Winters A, Moulton LH, Mulenga M, Norris DE, Moss WJ. The Impact of Household and Community Indoor Residual Spray Coverage with Fludora Fusion in a High Malaria Transmission Setting in Northern Zambia. Am J Trop Med Hyg 2023; 109:248-257. [PMID: 37364860 PMCID: PMC10397455 DOI: 10.4269/ajtmh.22-0440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 04/24/2023] [Indexed: 06/28/2023] Open
Abstract
Zambia's National Malaria Elimination Program transitioned to Fludora Fusion in 2019 for annual indoor residual spraying (IRS) in Nchelenge District, an area with holoendemic malaria transmission. Previously, IRS was associated with reductions in parasite prevalence during the rainy season only, presumably because of insufficient residual insecticide longevity. This study assessed the impact of transitioning from Actellic 300CS to long-acting Fludora Fusion using active surveillance data from 2014 through 2021. A difference-in-differences analysis estimated changes in rainy season parasite prevalence associated with living in a sprayed house, comparing insecticides. The change in the 2020 to 2021 dry season parasite prevalence associated with living in a house sprayed with Fludora Fusion was also estimated. Indoor residual spraying with Fludora Fusion was not associated with decreased rainy season parasite prevalence compared with IRS with Actellic 300CS (ratio of prevalence ratios [PRs], 1.09; 95% CI, 0.89-1.33). Moreover, living in a house sprayed with either insecticide was not associated with decreased malaria risk (Actellic 300CS: PR, 0.97; 95% CI, 0.86-1.10; Fludora Fusion: rainy season PR, 1.06; 95% CI, 0.89-1.25; dry season PR, 1.21; 95% CI, 0.99-1.48). In contrast, each 10% increase in community IRS coverage was associated with a 4% to 5% reduction in parasite prevalence (rainy season: PR, 0.95; 95% CI, 0.92-0.97; dry season: PR, 0.96; 95% CI, 0.94-0.99), suggesting a community-level protective effect, and corroborating the importance of high-intervention coverage.
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Affiliation(s)
- Ellen Ferriss
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | | | | | | | - Anna Winters
- Akros, Lusaka, Zambia
- University of Montana, Missoula, Montana
| | - Lawrence H. Moulton
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Pfizer Canada, Quebec, Canada
| | - Modest Mulenga
- Directorate of Research and Postgraduate Studies, Lusaka Apex Medical University, Lusaka, Zambia
| | - Douglas E. Norris
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - William J. Moss
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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Nyawanda BO, Beloconi A, Khagayi S, Bigogo G, Obor D, Otieno NA, Lange S, Franke J, Sauerborn R, Utzinger J, Kariuki S, Munga S, Vounatsou P. The relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya: A time-series analysis of monthly incidence data from 2008 to 2019. Parasite Epidemiol Control 2023; 21:e00297. [PMID: 37021322 PMCID: PMC10068258 DOI: 10.1016/j.parepi.2023.e00297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 03/07/2023] [Accepted: 03/12/2023] [Indexed: 03/17/2023] Open
Abstract
Background Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. Methods Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. Results Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59-0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10-1.44). Bed net use was associated with a decline in malaria incidence in children aged 6-59 months (IRR = 0.78, 95% BCI: 0.70-0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. Conclusions Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6-59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.
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Lubinda J, Bi Y, Haque U, Lubinda M, Hamainza B, Moore AJ. Spatio-temporal monitoring of health facility-level malaria trends in Zambia and adaptive scaling for operational intervention. Commun Med 2022; 2:79. [PMID: 35789566 PMCID: PMC9249860 DOI: 10.1038/s43856-022-00144-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/15/2022] [Indexed: 12/02/2022] Open
Abstract
Background The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies. Methods This study developed intelligent data analytics incorporating Bayesian trend and spatio-temporal Integrated Laplace Approximation models to analyse high-burden over 32 million reported malaria cases from 1743 health facilities in Zambia between 2009 and 2015. Results The results show that at least 5.4 million people live in catchment areas with increasing trends of malaria, covering over 47% of all health facilities, while 5.7 million people live in areas with a declining trend (95% CI), covering 27% of health facilities. A two-scale spatio-temporal trend comparison identified significant differences between health facilities and higher-level districts, and the pattern observed in the southeastern region of Zambia provides the first evidence of the impact of recently implemented localised interventions. Conclusions The results support our recommendation for an adaptive scaling approach when implementing national malaria monitoring, control and elimination strategies and a particular need for stratified subnational approaches targeting high-burden regions with increasing disease trends. Strong clusters along borders with highly endemic countries in the north and south of Zambia underscore the need for coordinated cross-border malaria initiatives and strategies. Malaria is an infectious disease that is widespread in many African countries. Malaria transmission within a country can vary between regions, so tailored interventions for malaria control and elimination targeted to different regions are necessary. To achieve this, it is important to measure and monitor the frequency of malaria infections, its risk, and trends at different geographic administrative scales. This study analysed over 32 million reported malaria cases from 1743 health facilities in Zambia between 2009 and 2015. The results showed an increasing national trend in malaria risk and malaria infection frequency and identified differences between health facility and district trends. These findings support a flexible approach when implementing and expanding national malaria monitoring, control and elimination strategies, especially in areas bordering countries where malaria is widespread, cross-border movement is common, and cross-border initiatives could be beneficial. Lubinda et al. analyse over 32 million health-facility reported malaria cases in Zambia (2009–15) to examine spatially-structured temporal trends. They observe overall increasing trends in risk and rates and highlight the potential benefits of using an adaptive scaling approach in national malaria strategies, and a need for cross-border initiatives.
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Carrasco-Escobar G, Qquellon J, Villa D, Cava R, Llanos-Cuentas A, Benmarhnia T. Time-Varying Effects of Meteorological Variables on Malaria Epidemiology in the Context of Interrupted Control Efforts in the Amazon Rainforest, 2000-2017. Front Med (Lausanne) 2021; 8:721515. [PMID: 34660633 PMCID: PMC8511324 DOI: 10.3389/fmed.2021.721515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 08/27/2021] [Indexed: 11/25/2022] Open
Abstract
Successful malaria control interventions, mostly based on the training of health workers, distribution of insecticide-treated nets, and spraying, decrease malaria incidence; however, when these interventions are interrupted, a resurgence may occur. In the Peruvian Amazon, after discontinuing the control activities implemented by the PAMAFRO project (2006–2010)-a Global Fund-sponsored project for the strengthening of malaria control and surveillance in multiple countries in Latin America– malaria cases re-emerged dramatically. In parallel, meteorological factors determine the conditions suitable for the development, reproduction, and survival of mosquito vectors and parasites. This study hypothesized that interruption of malaria interventions may have modified the meteorological-malaria relationships over time (i.e., temporal changes in the dose-response between meteorological variables and malaria incidence). In this panel data analysis, we assessed the extent that relationships between meteorological variables and malaria changed temporally using data of monthly malaria incidence due to Plasmodium vivax or P. falciparum in Loreto, Peru (2000–2017). Generalized additive models were used to explore how the effects of meteorological variables changed in magnitude before, during, and after the PAMAFRO intervention. We found that once the PAMAFRO intervention had been interrupted, the estimated effects (dose-response) of meteorological variables on incidence rates decreased for both malaria parasite species. However, these fitted effect estimates did not reach their baseline levels (before the PAMAFRO period); variations of time-varying slopes between 0.45 and 2.07 times were observed after the PAMAFRO intervention. We also reported significant heterogeneity in the geographical distributions of malaria, parasite species, and meteorological variables. High malaria transmission occurred consistently in the northwestern provinces of Loreto Department. Since the end of the PAMAFRO period, a higher effect of precipitation and actual evapotranspiration was described on P. falciparum compared to P. vivax. The effect of temperature on malaria was greater over a shorter time (1-month lag or less), compared with precipitation and actual evapotranspiration (12-month lag). These findings demonstrate the importance of sustained malaria control efforts since interruption may enhance the links between meteorological factors and malaria. Our results also emphasize the importance of considering the time-varying effect of meteorological factors on malaria incidence to tailor control interventions, especially to better manage the current and future climate change crisis.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Jazmin Qquellon
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Diego Villa
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Renato Cava
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alejandro Llanos-Cuentas
- Facultad de Salud Pública y Administración, Universidad Peruana Cayetano Heredia, Lima, Peru.,Instituto de Medicina Tropical "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Tarik Benmarhnia
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States.,Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA, United States
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6
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Odhiambo JN, Kalinda C, Macharia PM, Snow RW, Sartorius B. Spatial and spatio-temporal methods for mapping malaria risk: a systematic review. BMJ Glob Health 2021; 5:bmjgh-2020-002919. [PMID: 33023880 PMCID: PMC7537142 DOI: 10.1136/bmjgh-2020-002919] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 08/23/2020] [Accepted: 08/24/2020] [Indexed: 12/21/2022] Open
Abstract
Background Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA). Methods A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion. Results One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7–16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach. Conclusions Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology.
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Affiliation(s)
| | - Chester Kalinda
- Discipline of Public Health Medicine, University of KwaZulu-Natal, Durban, South Africa.,Faculty of Agriculture and Natural Resources, University of Namibia, Windhoek, Namibia
| | - Peter M Macharia
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Robert W Snow
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.,Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Benn Sartorius
- Discipline of Public Health Medicine, University of KwaZulu-Natal, Durban, South Africa.,Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
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7
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Lubinda J, Haque U, Bi Y, Shad MY, Keellings D, Hamainza B, Moore AJ. Climate change and the dynamics of age-related malaria incidence in Southern Africa. Environ Res 2021; 197:111017. [PMID: 33766570 DOI: 10.1016/j.envres.2021.111017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 02/27/2021] [Accepted: 03/11/2021] [Indexed: 06/12/2023]
Abstract
In the last decade, many malaria-endemic countries, like Zambia, have achieved significant reductions in malaria incidence among children <5 years old but face ongoing challenges in achieving similar progress against malaria in older age groups. In parts of Zambia, changing climatic and environmental factors are among those suspectedly behind high malaria incidence. Changes and variations in these factors potentially interfere with intervention program effectiveness and alter the distribution and incidence patterns of malaria differentially between young children and the rest of the population. We used parametric and non-parametric statistics to model the effects of climatic and socio-demographic variables on age-specific malaria incidence vis-à-vis control interventions. Linear regressions, mixed models, and Mann-Kendall tests were implemented to explore trends, changes in trends, and regress malaria incidence against environmental and intervention variables. Our study shows that while climate parameters affect the whole population, their impacts are felt most by people aged ≥5 years. Climate variables influenced malaria substantially more than mosquito nets and indoor residual spraying interventions. We establish that climate parameters negatively impact malaria control efforts by exacerbating the transmission conditions via more conducive temperature and rainfall environments, which are augmented by cultural and socioeconomic exposure mechanisms. We argue that an intensified communications and education intervention strategy for behavioural change specifically targeted at ≥5 aged population where incidence rates are increasing, is urgently required and call for further malaria stratification among the ≥5 age groups in the routine collection, analysis and reporting of malaria mortality and incidence data.
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Affiliation(s)
- Jailos Lubinda
- School of Geography and Environmental Sciences, Ulster University, Coleraine, UK; School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom; School of Nursing, Faculty of Life & Health Sciences, Jordanstown, Newtownabbey, United Kingdom.
| | - Ubydul Haque
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Centre, Fort Worth, TX, 76107, USA; Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Yaxin Bi
- School of Computing, Ulster University, Jordanstown, Newtownabbey, UK
| | | | - David Keellings
- Department of Geography, University of Alabama, Tuscaloosa, AL, USA
| | - Busiku Hamainza
- Ministry of Health, National Malaria Elimination Center, Lusaka, Zambia
| | - Adrian J Moore
- School of Geography and Environmental Sciences, Ulster University, Coleraine, UK
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8
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Keating J, Yukich JO, Miller JM, Scates S, Hamainza B, Eisele TP, Bennett A. Retrospective evaluation of the effectiveness of indoor residual spray with pirimiphos-methyl (Actellic) on malaria transmission in Zambia. Malar J 2021; 20:173. [PMID: 33794892 PMCID: PMC8017828 DOI: 10.1186/s12936-021-03710-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 03/24/2021] [Indexed: 11/27/2022] Open
Abstract
Background Widespread insecticide resistance to pyrethroids could thwart progress towards elimination. Recently, the World Health Organization has encouraged the use of non-pyrethroid insecticides to reduce the spread of insecticide resistance. An electronic tool for implementing and tracking coverage of IRS campaigns has recently been tested (mSpray), using satellite imagery to improve the accuracy and efficiency of the enumeration process. The purpose of this paper is to retrospectively analyse cross-sectional observational data to provide evidence of the epidemiological effectiveness of having introduced Actellic 300CS and the mSpray platform into IRS programmes across Zambia. Methods Health facility catchment areas in 40 high burden districts in 5 selected provinces were initially targeted for spraying. The mSpray platform was used in 7 districts in Luapula Province. An observational study design was used to assess the relationship between IRS exposure and confirmed malaria case incidence. A random effects Poisson model was used to quantify the effect of IRS (with and without use of the mSpray platform) on confirmed malaria case incidence over the period 2013–2017; analysis was restricted to the 4 provinces where IRS was conducted in each year 2014–2016. Results IRS was conducted in 283 health facility catchment areas from 2014 to 2016; 198 health facilities from the same provinces, that received no IRS during this period, served as a comparison. IRS appears to be associated with reduced confirmed malaria incidence; the incidence rate ratio (IRR) was lower in areas with IRS but without mSpray, compared to areas with no IRS (IRR = 0.91, 95% CI 0.84–0.98). Receiving IRS with mSpray significantly lowered confirmed case incidence (IRR = 0.75, 95% CI 0.66–0.86) compared to no IRS. IRS with mSpray resulted in lower incidence compared to IRS without mSpray (IRR = 0.83, 95% CI 0.72–0.95). Conclusions IRS using Actellic-CS appears to substantially reduce malaria incidence in Zambia. The use of the mSpray tool appears to improve the effectiveness of the IRS programme, possibly through improved population level coverage. The results of this study lend credence to the anecdotal evidence of the effectiveness of 3GIRS using Actellic, and the importance of exploring new platforms for improving effective population coverage of areas targeted for spraying.
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Affiliation(s)
- Joseph Keating
- Center for Applied Malaria Research and Evaluation, Department of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2320, New Orleans, 70112, USA.
| | - Joshua O Yukich
- Center for Applied Malaria Research and Evaluation, Department of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2320, New Orleans, 70112, USA
| | - John M Miller
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), National Malaria Elimination Centre, Chainama Hospital College Grounds, Lusaka, Zambia
| | - Sara Scates
- Center for Applied Malaria Research and Evaluation, Department of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2320, New Orleans, 70112, USA
| | - Busiku Hamainza
- National Malaria Elimination Centre, Ministry of Health, Lusaka, Zambia
| | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Department of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2320, New Orleans, 70112, USA
| | - Adam Bennett
- Global Health Sciences, University of California, San Francisco, CA, USA
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9
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Lubinda J, Bi Y, Hamainza B, Haque U, Moore AJ. Modelling of malaria risk, rates, and trends: A spatiotemporal approach for identifying and targeting sub-national areas of high and low burden. PLoS Comput Biol 2021; 17:e1008669. [PMID: 33647029 PMCID: PMC7951982 DOI: 10.1371/journal.pcbi.1008669] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 03/11/2021] [Accepted: 01/04/2021] [Indexed: 01/16/2023] Open
Abstract
While mortality from malaria continues to decline globally, incidence rates in many countries are rising. Within countries, spatial and temporal patterns of malaria vary across communities due to many different physical and social environmental factors. To identify those areas most suitable for malaria elimination or targeted control interventions, we used Bayesian models to estimate the spatiotemporal variation of malaria risk, rates, and trends to determine areas of high or low malaria burden compared to their geographical neighbours. We present a methodology using Bayesian hierarchical models with a Markov Chain Monte Carlo (MCMC) based inference to fit a generalised linear mixed model with a conditional autoregressive structure. We modelled clusters of similar spatiotemporal trends in malaria risk, using trend functions with constrained shapes and visualised high and low burden districts using a multi-criterion index derived by combining spatiotemporal risk, rates and trends of districts in Zambia. Our results indicate that over 3 million people in Zambia live in high-burden districts with either high mortality burden or high incidence burden coupled with an increasing trend over 16 years (2000 to 2015) for all age, under-five and over-five cohorts. Approximately 1.6 million people live in high-incidence burden areas alone. Using our method, we have developed a platform that can enable malaria programs in countries like Zambia to target those high-burden areas with intensive control measures while at the same time pursue malaria elimination efforts in all other areas. Our method enhances conventional approaches and measures to identify those districts which had higher rates and increasing trends and risk. This study provides a method and a means that can help policy makers evaluate intervention impact over time and adopt appropriate geographically targeted strategies that address the issues of both high-burden areas, through intensive control approaches, and low-burden areas, via specific elimination programs.
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Affiliation(s)
- Jailos Lubinda
- School of Geography and Environmental Sciences, Ulster University, Coleraine, United Kingdom
- School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom
| | - Yaxin Bi
- School of Computing, Ulster University, Newtownabbey, United Kingdom
| | - Busiku Hamainza
- Ministry of Health, National Malaria Elimination Centre, Lusaka, Zambia
| | - Ubydul Haque
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Centre, Fort Worth, Texas, United States of America
- Department of Geography, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Adrian J. Moore
- School of Geography and Environmental Sciences, Ulster University, Coleraine, United Kingdom
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Lubinda J, Haque U, Bi Y, Hamainza B, Moore AJ. Near-term climate change impacts on sub-national malaria transmission. Sci Rep 2021; 11:751. [PMID: 33436862 DOI: 10.1038/s41598-020-80432-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 12/17/2020] [Indexed: 01/29/2023] Open
Abstract
The role of climate change on global malaria is often highlighted in World Health Organisation reports. We modelled a Zambian socio-environmental dataset from 2000 to 2016, against malaria trends and investigated the relationship of near-term environmental change with malaria incidence using Bayesian spatio-temporal, and negative binomial mixed regression models. We introduced the diurnal temperature range (DTR) as an alternative environmental measure to the widely used mean temperature. We found substantial sub-national near-term variations and significant associations with malaria incidence-trends. Significant spatio-temporal shifts in DTR/environmental predictors influenced malaria incidence-rates, even in areas with declining trends. We highlight the impact of seasonally sensitive DTR, especially in the first two quarters of the year and demonstrate how substantial investment in intervention programmes is negatively impacted by near-term climate change, most notably since 2010. We argue for targeted seasonally-sensitive malaria chemoprevention programmes.
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11
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Manda S, Haushona N, Bergquist R. A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa. Int J Environ Res Public Health 2020; 17:E3070. [PMID: 32354095 PMCID: PMC7246597 DOI: 10.3390/ijerph17093070] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 04/01/2020] [Accepted: 04/03/2020] [Indexed: 01/03/2023]
Abstract
Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.
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Affiliation(s)
- Samuel Manda
- Biostatistics Research Unit, South African Medical Research Council, Pretoria 0001, South Africa
- Department of Statistics, University of Pretoria, Pretoria 0002, South Africa
- School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg 3209, South Africa
| | - Ndamonaonghenda Haushona
- Biostatistics Research Unit, South African Medical Research Council, Pretoria 0001, South Africa
- Division of Epidemiology and Biostatistics, University of Stellenbosch, Cape Town 8000, South Africa
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12
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Fouque F, Reeder JC. Impact of past and on-going changes on climate and weather on vector-borne diseases transmission: a look at the evidence. Infect Dis Poverty 2019; 8:51. [PMID: 31196187 PMCID: PMC6567422 DOI: 10.1186/s40249-019-0565-1] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 06/03/2019] [Indexed: 12/30/2022] Open
Abstract
Background The climate variables that directly influence vector-borne diseases’ ecosystems are mainly temperature and rainfall. This is not only because the vectors bionomics are strongly dependent upon these variables, but also because most of the elements of the systems are impacted, such as the host behavior and development and the pathogen amplification. The impact of the climate changes on the transmission patterns of these diseases is not easily understood, since many confounding factors are acting together. Consequently, knowledge of these impacts is often based on hypothesis derived from mathematical models. Nevertheless, some direct evidences can be found for several vector-borne diseases. Main body Evidences of the impact of climate change are available for malaria, arbovirus diseases such as dengue, and many other parasitic and viral diseases such as Rift Valley Fever, Japanese encephalitis, human African trypanosomiasis and leishmaniasis. The effect of temperature and rainfall change as well as extreme events, were found to be the main cause for outbreaks and are alarming the global community. Among the main driving factors, climate strongly influences the geographical distribution of insect vectors, which is rapidly changing due to climate change. Further, in both models and direct evidences, climate change is seen to be affecting vector-borne diseases more strikingly in fringe of different climatic areas often in the border of transmission zones, which were once free of these diseases with human populations less immune and more receptive. The impact of climate change is also more devastating because of the unpreparedness of Public Health systems to provide adequate response to the events, even when climatic warning is available. Although evidences are strong at the regional and local levels, the studies on impact of climate change on vector-borne diseases and health are producing contradictory results at the global level. Conclusions In this paper we discuss the current state of the results and draw on evidences from malaria, dengue and other vector-borne diseases to illustrate the state of current thinking and outline the need for further research to inform our predictions and response. Electronic supplementary material The online version of this article (10.1186/s40249-019-0565-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Florence Fouque
- UNICEF/UNDP/ World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), 20 Avenue Appia, 1211, Geneva 27, Switzerland.
| | - John C Reeder
- UNICEF/UNDP/ World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), 20 Avenue Appia, 1211, Geneva 27, Switzerland
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13
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Sadoine ML, Smargiassi A, Ridde V, Tusting LS, Zinszer K. The associations between malaria, interventions, and the environment: a systematic review and meta-analysis. Malar J 2018; 17:73. [PMID: 29415721 PMCID: PMC5803989 DOI: 10.1186/s12936-018-2220-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 01/31/2018] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Malaria transmission is driven by multiple factors, including complex and multifaceted connections between malaria transmission, socioeconomic conditions, climate and interventions. Forecasting models should account for all significant drivers of malaria incidence although it is first necessary to understand the relationship between malaria burden and the various determinants of risk to inform the development of forecasting models. In this study, the associations between malaria risk, environmental factors, and interventions were evaluated through a systematic review. METHODS Five electronic databases (CAB Abstracts, EMBASE, Global Health, MEDLINE and ProQuest Dissertations & Theses) were searched for studies that included both the effects of the environment and interventions on malaria within the same statistical model. Studies were restricted to quantitative analyses and health outcomes of malaria mortality or morbidity, outbreaks, or transmission suitability. Meta-analyses were conducted on a subset of results using random-effects models. RESULTS Eleven studies of 2248 potentially relevant articles that met inclusion criteria were identified for the systematic review and two meta-analyses based upon five results each were performed. Normalized Difference Vegetation Index was not found to be statistically significant associated with malaria with a pooled OR of 1.10 (95% CI 0.07, 1.71). Bed net ownership was statistically associated with decreasing risk of malaria, when controlling for the effects of environment with a pooled OR of 0.75 (95% CI 0.60, 0.95). In general, environmental effects on malaria, while controlling for the effect of interventions, were variable and showed no particular pattern. Bed nets ownership, use and distribution, have a significant protective effect while controlling for environmental variables. CONCLUSIONS There are a limited number of studies which have simultaneously evaluated both environmental and interventional effects on malaria risk. Poor statistical reporting and a lack of common metrics were important challenges for this review, which must be addressed to ensure reproducibility and quality research. A comprehensive or inclusive approach to identifying malaria determinants using standardized indicators would allow for a better understanding of its epidemiology, which is crucial to improve future malaria risk estimations.
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Affiliation(s)
- Margaux L Sadoine
- Université de Montréal Public Health Research Institute (Institut de Recherche en Santé Publique (IRSPUM)), Université de Montréal, Montréal, QC, Canada.
- School of Public Health, Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada.
| | - Audrey Smargiassi
- Université de Montréal Public Health Research Institute (Institut de Recherche en Santé Publique (IRSPUM)), Université de Montréal, Montréal, QC, Canada
- School of Public Health, Department of Environmental and Occupational Health, Université de Montréal, Montréal, QC, Canada
- Institut national de santé publique du Québec, Montréal, QC, Canada
| | - Valéry Ridde
- Université de Montréal Public Health Research Institute (Institut de Recherche en Santé Publique (IRSPUM)), Université de Montréal, Montréal, QC, Canada
- School of Public Health, Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
| | - Lucy S Tusting
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Kate Zinszer
- Université de Montréal Public Health Research Institute (Institut de Recherche en Santé Publique (IRSPUM)), Université de Montréal, Montréal, QC, Canada
- School of Public Health, Department of Social and Preventive Medicine, Université de Montréal, Montréal, QC, Canada
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14
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Weber GE, White MT, Babakhanyan A, Sumba PO, Vulule J, Ely D, John C, Angov E, Lanar D, Dutta S, Narum DL, Horii T, Cowman A, Beeson J, Smith J, Kazura JW, Dent AE. Sero-catalytic and Antibody Acquisition Models to Estimate Differing Malaria Transmission Intensities in Western Kenya. Sci Rep 2017; 7:16821. [PMID: 29203846 PMCID: PMC5715086 DOI: 10.1038/s41598-017-17084-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 11/21/2017] [Indexed: 12/19/2022] Open
Abstract
We sought to identify a subset of Plasmodium falciparum antibody targets that would inform monitoring efforts needed to eliminate malaria in high transmission settings. IgG antibodies to 28 recombinant Pf antigens were measured in residents of two communities in western Kenya examined in 2003 and 2013, when the respective prevalence of asymptomatic parasitemia among children was 81 and 15 percent by microscopy. Annual seroconversion rates based on a sero-catalytic model that dichotomised antibody values to negative versus positive showed that rates were higher in 2003 than 2013 for 1 pre-erythrocytic and 7 blood-stage antigens. Antibody acquisition models that considered antibody levels as continuous variables showed that age-related antibody levels to Circumsporozoite Protein and 10 merozoite proteins increased at different rates with age in 2003 versus 2013. Both models found that antibodies to 5 proteins of the Merozoite Surface Protein 1 complex were differentially acquired between the cohorts, and that changes in antibody levels to Apical Membrane Antigen 1 suggested a decrease in transmission that occurred ~10 years before 2013. Further studies evaluating antibodies to this subset of Pf antigens as biomarkers of malaria exposure and naturally acquired immunity are warranted in endemic settings where transmission has been reduced but persists.
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Affiliation(s)
- Grace E Weber
- Center for Global Health and Diseases, Case Western Reserve University, Cleveland, OH, USA.,Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | | | - Anna Babakhanyan
- Center for Global Health and Diseases, Case Western Reserve University, Cleveland, OH, USA
| | | | - John Vulule
- Kenya Medical Research Institute, Kisumu, Kenya
| | - Dylan Ely
- Center for Global Health and Diseases, Case Western Reserve University, Cleveland, OH, USA
| | - Chandy John
- Department of Pediatrics, Riley Hospital, Indiana University, Indianapolis, IN, USA
| | - Evelina Angov
- Malaria Vaccine Branch, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - David Lanar
- Malaria Vaccine Branch, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - Sheetij Dutta
- Malaria Vaccine Branch, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - David L Narum
- Laboratory of Malaria Immunology and Vaccinology, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA
| | - Toshihiro Horii
- Department of Molecular Protozoology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan
| | - Alan Cowman
- Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | | | - Joseph Smith
- Center for Infectious Disease Research, Seattle, WA, USA
| | - James W Kazura
- Center for Global Health and Diseases, Case Western Reserve University, Cleveland, OH, USA.
| | - Arlene E Dent
- Center for Global Health and Diseases, Case Western Reserve University, Cleveland, OH, USA.,Department of Pediatrics, Rainbow Babies and Children's Hospital, Cleveland, OH, USA
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15
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Cohen JM, Le Menach A, Pothin E, Eisele TP, Gething PW, Eckhoff PA, Moonen B, Schapira A, Smith DL. Mapping multiple components of malaria risk for improved targeting of elimination interventions. Malar J 2017; 16:459. [PMID: 29132357 PMCID: PMC5683539 DOI: 10.1186/s12936-017-2106-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 11/02/2017] [Indexed: 11/13/2022] Open
Abstract
There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.
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Affiliation(s)
- Justin M Cohen
- Clinton Health Access Initiative, 383 Dorchester Ave., Suite 400, Boston, MA, 02127, USA.
| | - Arnaud Le Menach
- Clinton Health Access Initiative, 383 Dorchester Ave., Suite 400, Boston, MA, 02127, USA
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051, Basel, Switzerland
| | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal St (2300), New Orleans, LA, 70112, USA
| | - Peter W Gething
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LF, UK
| | - Philip A Eckhoff
- Institute for Disease Modeling, Building IV, 3150 139th Ave SE, Bellevue, WA, 98005, USA
| | - Bruno Moonen
- Bill & Melinda Gates Foundation, PO Box 23350, Seattle, WA, 98102, USA
| | | | - David L Smith
- Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave., Suite 600, Seattle, WA, 98121, USA
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16
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Thomson MC, Ukawuba I, Hershey CL, Bennett A, Ceccato P, Lyon B, Dinku T. Using Rainfall and Temperature Data in the Evaluation of National Malaria Control Programs in Africa. Am J Trop Med Hyg 2017; 97:32-45. [PMID: 28990912 PMCID: PMC5619931 DOI: 10.4269/ajtmh.16-0696] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 12/29/2016] [Indexed: 11/17/2022] Open
Abstract
Since 2010, the Roll Back Malaria (RBM) Partnership, including National Malaria Control Programs, donor agencies (e.g., President's Malaria Initiative and Global Fund), and other stakeholders have been evaluating the impact of scaling up malaria control interventions on all-cause under-five mortality in several countries in sub-Saharan Africa. The evaluation framework assesses whether the deployed interventions have had an impact on malaria morbidity and mortality and requires consideration of potential nonintervention influencers of transmission, such as drought/floods or higher temperatures. Herein, we assess the likely effect of climate on the assessment of the impact malaria interventions in 10 priority countries/regions in eastern, western, and southern Africa for the President's Malaria Initiative. We used newly available quality controlled Enhanced National Climate Services rainfall and temperature products as well as global climate products to investigate likely impacts of climate on malaria evaluations and test the assumption that changing the baseline period can significantly impact on the influence of climate in the assessment of interventions. Based on current baseline periods used in national malaria impact assessments, we identify three countries/regions where current evaluations may overestimate the impact of interventions (Tanzania, Zanzibar, Uganda) and three countries where current malaria evaluations may underestimate the impact of interventions (Mali, Senegal and Ethiopia). In four countries (Rwanda, Malawi, Mozambique, and Angola) there was no strong difference in climate suitability for malaria in the pre- and post-intervention period. In part, this may be due to data quality and analysis issues.
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Affiliation(s)
- Madeleine C. Thomson
- International Research Institute for Climate and Society, Palisades, New York
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York
| | - Israel Ukawuba
- International Research Institute for Climate and Society, Palisades, New York
| | - Christine L. Hershey
- President's Malaria Initiative, United States Agency for International Development, Washington, District of Columbia
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, California
| | - Pietro Ceccato
- International Research Institute for Climate and Society, Palisades, New York
| | - Bradfield Lyon
- International Research Institute for Climate and Society, Palisades, New York
| | - Tufa Dinku
- International Research Institute for Climate and Society, Palisades, New York
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Comfort A, Leegwater A, Nakhimovsky S, Kansembe H, Hamainza B, Bwalya B, Alilio M, Johns B, Olsho L. Exploring the use of routinely-available, retrospective data to study the association between malaria control scale-up and micro-economic outcomes in Zambia. Malar J 2017; 16:15. [PMID: 28052759 PMCID: PMC5209918 DOI: 10.1186/s12936-016-1665-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Accepted: 12/21/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Country-level evidence on the impact of malaria control on micro-economic outcomes is vital for mobilizing domestic and donor resources for malaria control. Using routinely available survey data could facilitate this investigation in a cost-efficient way. METHODS The authors used Malaria Indicator Surveys (MIS) and Living Conditions Monitoring Survey (LCMS) data from 2006 to 2010 for all 72 districts in Zambia to relate malaria control scale-up with household food spending (proxy for household well-being), educational attainment and agricultural production. The authors used two quasi-experimental designs: (1) a generalized propensity score for a continuous treatment variable (defined as coverage from owning insecticide-treated bed nets and/or receipt of indoor residual spraying); and, (2) a district fixed effects model to assess changes in the outcome relative to changes in treatment pre-post scale-up. The unit of analysis was at district level. The authors also conducted simulations post-analysis to assess statistical power. RESULTS Micro-economic outcomes increased (33% increase in food spending) concurrently with malaria control coverage (62% increase) from 2006 to 2010. Despite using data from all 72 districts, both analytic methods yielded wide confidence intervals that do not conclusively link outcomes and malaria control coverage increases. The authors cannot rule out positive, null or negative effects. The upper bound estimates of the results show that if malaria control coverage increases from 60 to 70%, food spending could increase up to 14%, maize production could increase up to 57%, and years of schooling could increase up to 0.5 years. Simulations indicated that the generalized propensity score model did not have good statistical power. CONCLUSION While it is technically possible to use routinely available survey data to relate malaria control scale-up and micro-economic outcomes, it is not clear from this analysis that meaningful results can be obtained when survey data are highly aggregated. Researchers in similar settings should assess the feasibility of disaggregating existing survey data. Additionally, large surveys, such as LCMS and MIS, could incorporate data on both malaria coverage and household expenditures, respectively.
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Affiliation(s)
- Alison Comfort
- Health Finance and Governance Project, Abt Associates Inc., Bethesda, USA
| | - Anthony Leegwater
- Health Finance and Governance Project, Abt Associates Inc., Bethesda, USA.
| | - Sharon Nakhimovsky
- Health Finance and Governance Project, Abt Associates Inc., Bethesda, USA
| | - Henry Kansembe
- National Malaria Control Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Busiku Hamainza
- National Malaria Control Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Benson Bwalya
- International Health Division, Abt Associates Inc., Lusaka, Zambia
| | - Martin Alilio
- President's Malaria Initiative, Washington, D.C., USA
| | - Ben Johns
- Health Finance and Governance Project, Abt Associates Inc., Bethesda, USA
| | - Lauren Olsho
- U.S. Health Division, Abt Associates Inc., Cambridge, USA
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