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Thawer SG, Golumbeanu M, Lazaro S, Chacky F, Munisi K, Aaron S, Molteni F, Lengeler C, Pothin E, Snow RW, Alegana VA. Spatio-temporal modelling of routine health facility data for malaria risk micro-stratification in mainland Tanzania. Sci Rep 2023; 13:10600. [PMID: 37391538 PMCID: PMC10313820 DOI: 10.1038/s41598-023-37669-x] [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: 10/25/2022] [Accepted: 06/26/2023] [Indexed: 07/02/2023] Open
Abstract
As malaria transmission declines, the need to monitor the heterogeneity of malaria risk at finer scales becomes critical to guide community-based targeted interventions. Although routine health facility (HF) data can provide epidemiological evidence at high spatial and temporal resolution, its incomplete nature of information can result in lower administrative units without empirical data. To overcome geographic sparsity of data and its representativeness, geo-spatial models can leverage routine information to predict risk in un-represented areas as well as estimate uncertainty of predictions. Here, a Bayesian spatio-temporal model was applied on malaria test positivity rate (TPR) data for the period 2017-2019 to predict risks at the ward level, the lowest decision-making unit in mainland Tanzania. To quantify the associated uncertainty, the probability of malaria TPR exceeding programmatic threshold was estimated. Results showed a marked spatial heterogeneity in malaria TPR across wards. 17.7 million people resided in areas where malaria TPR was high (≥ 30; 90% certainty) in the North-West and South-East parts of Tanzania. Approximately 11.7 million people lived in areas where malaria TPR was very low (< 5%; 90% certainty). HF data can be used to identify different epidemiological strata and guide malaria interventions at micro-planning units in Tanzania. These data, however, are imperfect in many settings in Africa and often require application of geo-spatial modelling techniques for estimation.
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Affiliation(s)
- Sumaiyya G Thawer
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Monica Golumbeanu
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Samwel Lazaro
- Ministry of Health, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Frank Chacky
- Ministry of Health, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Khalifa Munisi
- Ministry of Health, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Sijenunu Aaron
- Ministry of Health, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Fabrizio Molteni
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- National Malaria Control Programme, Dodoma, Tanzania
| | - Christian Lengeler
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Clinton Health Access Initiative, New York, USA
| | - Robert W Snow
- Population Health Unit, KEMRI-Welcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Victor A Alegana
- World Health Organization, Regional Office for Africa, Brazzaville, Republic of Congo
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Ashton RA, Hamainza B, Lungu C, Rutagwera MRI, Porter T, Bennett A, Hainsworth M, Burnett S, Silumbe K, Slater H, Eisele TP, Miller JM. Effectiveness of community case management of malaria on severe malaria and inpatient malaria deaths in Zambia: a dose-response study using routine health information system data. Malar J 2023; 22:96. [PMID: 36927440 PMCID: PMC10022244 DOI: 10.1186/s12936-023-04525-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 03/07/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Community case management of malaria (CCM) has been expanded in many settings, but there are limited data describing the impact of these services in routine implementation settings or at large scale. Zambia has intensively expanded CCM since 2013, whereby trained volunteer community health workers (CHW) use rapid diagnostic tests and artemether-lumefantrine to diagnose and treat uncomplicated malaria. METHODS This retrospective, observational study explored associations between changing malaria service point (health facility or CHW) density per 1000 people and severe malaria admissions or malaria inpatient deaths by district and month in a dose-response approach, using existing routine and programmatic data. Negative binomial generalized linear mixed-effect models were used to assess the impact of increasing one additional malaria service point per 1000 population, and of achieving Zambia's interim target of 1 service point per 750 population. Access to insecticide-treated nets, indoor-residual spraying, and rainfall anomaly were included in models to reduce potential confounding. RESULTS The study captured 310,855 malaria admissions and 7158 inpatient malaria deaths over 83 districts (seven provinces) from January 2015 to May 2020. Total CHWs increased from 43 to 4503 during the study period, while health facilities increased from 1263 to 1765. After accounting for covariates, an increase of one malaria service point per 1000 was associated with a 19% reduction in severe malaria admissions among children under five (incidence rate ratio [IRR] 0.81, 95% confidence interval [CI] 0.75-0.87, p < 0.001) and 23% reduction in malaria deaths among under-fives (IRR 0.77, 95% CI 0.66-0.91). After categorizing the exposure of population per malaria service point, there was evidence for an effect on malaria admissions and inpatient malaria deaths among children under five only when reaching the target of one malaria service point per 750 population. CONCLUSIONS CCM is an effective strategy for preventing severe malaria and deaths in areas such as Zambia where malaria diagnosis and treatment access remains challenging. These results support the continued investment in CCM scale-up in similar settings, to improve access to malaria diagnosis and treatment.
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Affiliation(s)
- Ruth A Ashton
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2300, New Orleans, LA, USA.
| | - Busiku Hamainza
- National Malaria Elimination Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Chris Lungu
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia
| | | | - Travis Porter
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2300, New Orleans, LA, USA
| | | | | | | | - Kafula Silumbe
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia
| | | | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2300, New Orleans, LA, USA
| | - John M Miller
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia
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Thawer SG, Golumbeanu M, Munisi K, Aaron S, Chacky F, Lazaro S, Mohamed A, Kisoka N, Lengeler C, Molteni F, Ross A, Snow RW, Pothin E. The use of routine health facility data for micro-stratification of malaria risk in mainland Tanzania. Malar J 2022; 21:345. [DOI: 10.1186/s12936-022-04364-7] [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: 07/12/2022] [Accepted: 11/05/2022] [Indexed: 11/19/2022] Open
Abstract
Abstract
Background
Current efforts to estimate the spatially diverse malaria burden in malaria-endemic countries largely involve the use of epidemiological modelling methods for describing temporal and spatial heterogeneity using sparse interpolated prevalence data from periodic cross-sectional surveys. However, more malaria-endemic countries are beginning to consider local routine data for this purpose. Nevertheless, routine information from health facilities (HFs) remains widely under-utilized despite improved data quality, including increased access to diagnostic testing and the adoption of the electronic District Health Information System (DHIS2). This paper describes the process undertaken in mainland Tanzania using routine data to develop a high-resolution, micro-stratification risk map to guide future malaria control efforts.
Methods
Combinations of various routine malariometric indicators collected from 7098 HFs were assembled across 3065 wards of mainland Tanzania for the period 2017–2019. The reported council-level prevalence classification in school children aged 5–16 years (PfPR5–16) was used as a benchmark to define four malaria risk groups. These groups were subsequently used to derive cut-offs for the routine indicators by minimizing misclassifications and maximizing overall agreement. The derived-cutoffs were converted into numbered scores and summed across the three indicators to allocate wards into their overall risk stratum.
Results
Of 3065 wards, 353 were assigned to the very low strata (10.5% of the total ward population), 717 to the low strata (28.6% of the population), 525 to the moderate strata (16.2% of the population), and 1470 to the high strata (39.8% of the population). The resulting micro-stratification revealed malaria risk heterogeneity within 80 councils and identified wards that would benefit from community-level focal interventions, such as community-case management, indoor residual spraying and larviciding.
Conclusion
The micro-stratification approach employed is simple and pragmatic, with potential to be easily adopted by the malaria programme in Tanzania. It makes use of available routine data that are rich in spatial resolution and that can be readily accessed allowing for a stratification of malaria risk below the council level. Such a framework is optimal for supporting evidence-based, decentralized malaria control planning, thereby improving the effectiveness and allocation efficiency of malaria control interventions.
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Pezzulo C, Alegana VA, Christensen A, Bakari O, Tatem AJ. Understanding factors associated with attending secondary school in Tanzania using household survey data. PLoS One 2022; 17:e0263734. [PMID: 35213555 PMCID: PMC8880958 DOI: 10.1371/journal.pone.0263734] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 01/25/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Sustainable Development Goal (SDG) 4 aims to ensure inclusive and equitable access for all by 2030, leaving no one behind. One indicator selected to measure progress towards achievement is the participation rate of youth in education (SDG 4.3.1). Here we aim to understand drivers of school attendance using one country in East Africa as an example. METHODS Nationally representative household survey data (2015-16 Tanzania Demographic and Health Survey) were used to explore individual, household and contextual factors associated with secondary school attendance in Tanzania. These included, age, head of household's levels of education, gender, household wealth index and total number of children under five. Contextual factors such as average pupil to qualified teacher ratio and geographic access to school were also tested at cluster level. A two-level random intercept logistic regression model was used in exploring association of these factors with attendance in a multi-level framework. RESULTS Age of household head, educational attainments of either of the head of the household or parent, child characteristics such as gender, were important predictors of secondary school attendance. Being in a richer household and with fewer siblings of lower age (under the age of 5) were associated with increased odds of attendance (OR = 0.91, CI 95%: 0.86; 0.96). Contextual factors were less likely to be associated with secondary school attendance. CONCLUSIONS Individual and household level factors are likely to impact secondary school attendance rates more compared to contextual factors, suggesting an increased focus of interventions at these levels is needed. Future studies should explore the impact of interventions targeting these levels. Policies should ideally promote gender equality in accessing secondary school as well as support those families where the dependency ratio is high. Strategies to reduce poverty will also increase the likelihood of attending school.
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Affiliation(s)
- Carla Pezzulo
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Victor A. Alegana
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- Population Health Unit, Kenya Medical Research Institute—Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Andrew Christensen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- Plan Denmark (PlanBørnefonden), Copenhagen, DK, United Kingdom
| | - Omar Bakari
- Tanzania DataLab (dLab), Dar es Salaam, Tanzania
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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5
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Epstein A, Maiteki-Sebuguzi C, Namuganga JF, Nankabirwa JI, Gonahasa S, Opigo J, Staedke SG, Rutazaana D, Arinaitwe E, Kamya MR, Bhatt S, Rodríguez-Barraquer I, Greenhouse B, Donnelly MJ, Dorsey G. Resurgence of malaria in Uganda despite sustained indoor residual spraying and repeated long lasting insecticidal net distributions. PLOS Glob Public Health 2022; 2:e0000676. [PMID: 36962736 PMCID: PMC10022262 DOI: 10.1371/journal.pgph.0000676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 07/27/2022] [Indexed: 11/19/2022]
Abstract
Five years of sustained indoor residual spraying (IRS) of insecticide from 2014 to 2019, first using a carbamate followed by an organophosphate, was associated with a marked reduction in the incidence of malaria in five districts of Uganda. We assessed changes in malaria incidence over an additional 21 months, corresponding to a change in IRS formulations using clothianidin with and without deltamethrin. Using enhanced health facility surveillance data, our objectives were to 1) estimate the impact of IRS on monthly malaria case counts at five surveillance sites over a 6.75 year period, and 2) compare monthly case counts at five facilities receiving IRS to ten facilities in neighboring districts not receiving IRS. For both objectives, we specified mixed effects negative binomial regression models with random intercepts for surveillance site adjusting for rainfall, season, care-seeking, and malaria diagnostic. Following the implementation of IRS, cases were 84% lower in years 4-5 (adjusted incidence rate ratio [aIRR] = 0.16, 95% CI 0.12-0.22), 43% lower in year 6 (aIRR = 0.57, 95% CI 0.44-0.74), and 39% higher in the first 9 months of year 7 (aIRR = 1.39, 95% CI 0.97-1.97) compared to pre-IRS levels. Cases were 67% lower in IRS sites than non-IRS sites in year 6 (aIRR = 0.33, 95% CI 0.17-0.63) but 38% higher in the first 9 months of year 7 (aIRR = 1.38, 95% CI 0.90-2.11). We observed a resurgence in malaria to pre-IRS levels despite sustained IRS. The timing of this resurgence corresponded to a change of active ingredient. Further research is needed to determine causality.
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Affiliation(s)
- Adrienne Epstein
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | | | | | - Joaniter I Nankabirwa
- Infectious Diseases Research Collaboration, Kampala, Uganda
- College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Jimmy Opigo
- National Malaria Control Division, Ministry of Health, Kampala, Uganda
| | - Sarah G Staedke
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Damian Rutazaana
- National Malaria Control Division, Ministry of Health, Kampala, Uganda
| | | | - Moses R Kamya
- Infectious Diseases Research Collaboration, Kampala, Uganda
- College of Health Sciences, Makerere University, Kampala, Uganda
| | - Samir Bhatt
- Department of Infectious Disease Epidemiology, Imperial College, St Mary's Hospital, London, United Kingdom
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Isabel Rodríguez-Barraquer
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Bryan Greenhouse
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Martin J Donnelly
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Grant Dorsey
- Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
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6
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Alegana VA, Macharia PM, Muchiri S, Mumo E, Oyugi E, Kamau A, Chacky F, Thawer S, Molteni F, Rutazanna D, Maiteki-Sebuguzi C, Gonahasa S, Noor AM, Snow RW. Plasmodium falciparum parasite prevalence in East Africa: Updating data for malaria stratification. PLOS Glob Public Health 2021; 1:e0000014. [PMID: 35211700 PMCID: PMC7612417 DOI: 10.1371/journal.pgph.0000014] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 11/15/2021] [Indexed: 11/18/2022]
Abstract
The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6-36.9) in Kenya, 10.6% (3.4-39.2) in mainland Tanzania, and 9.5% (4.0-48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (<1%) were inhabited by approximately 46.2 million people across the sub-region, or 52.2%, 26.7% and 10.4% of Kenya, mainland Tanzania and Uganda populations, respectively. In conclusion, parasite prevalence represents one of several data metrics for disease stratification at national and sub-national levels. To increase the use of this metric for decision making, there is a need to integrate other data layers on mortality related to malaria, malaria vector composition, insecticide resistance and bionomic, malaria care-seeking behaviour and current levels of unmet need of malaria interventions.
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Affiliation(s)
- Victor A. Alegana
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
- Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Peter M. Macharia
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
| | - Samuel Muchiri
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Eda Mumo
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Elvis Oyugi
- Division of National Malaria Programme, Ministry of Health, Nairobi, Kenya
| | - Alice Kamau
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Frank Chacky
- National Malaria Control Programme, Ministry of Health, Community Development, Gender, Elderly and Children, Dodoma, Tanzania
| | - Sumaiyya Thawer
- National Malaria Control Programme, Ministry of Health, Community Development, Gender, Elderly and Children, Dodoma, Tanzania
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Fabrizio Molteni
- National Malaria Control Programme, Ministry of Health, Community Development, Gender, Elderly and Children, Dodoma, Tanzania
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Damian Rutazanna
- National Malaria Control Division, Ministry of Health, Kampala, Uganda
| | - Catherine Maiteki-Sebuguzi
- National Malaria Control Division, Ministry of Health, Kampala, Uganda
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | | | - Abdisalan M. Noor
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - 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 Medicine, University of Oxford, Oxford, United Kingdom
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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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Nguefack-Tsague G, Tamfon BB, Ngnie-Teta I, Ngoufack MN, Keugoung B, Bataliack SM, Bilounga Ndongo C. Factors associated with the performance of routine health information system in Yaoundé-Cameroon: a cross-sectional survey. BMC Med Inform Decis Mak 2020; 20:339. [PMID: 33334340 PMCID: PMC7745475 DOI: 10.1186/s12911-020-01357-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [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: 05/14/2020] [Accepted: 11/30/2020] [Indexed: 11/14/2022] Open
Abstract
Background Routine Health Information Systems (RHIS) of low-income countries function below the globally expected standard, characterised by the production and use of poor-quality data, or the non-use of good quality data for informed decision making.
This has negatively influenced the health service delivery and uptake. This study focuses on identifying the factors associated with the performance of RHIS of the health facilities (HF) in Yaoundé, so as to guide targeted RHIS strengthening.
Methods A HF-based cross-sectional study in the 6 health districts (HDs) of Yaoundé was conducted. HFs were chosen using stratified sampling with probability proportional to size per HD. Data were collected, entered into Microsoft Excel 2013 and analysed with IBM- SPSS version 25. Consistency of the questionnaire was measured using Cronbach’s alpha coefficient. Pearson’s chi-square (and Fisher exact where relevant) tests were used to establish relationships between qualitative variables. Associations were further quantified using unadjusted Odd ratio (OR) for univariable analysis and adjusted odds ratio (aOR) for multivariable analysis with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant. Results Of 111 selected HFs; 16 (14.4%) were public and 95 (85.6%) private. Respondents aged 24–60 years with an average of 38.3 ± 9.3 years; 58 (52.3%) males and 53(47.7%) females. Cronbach’s alpha was 0.96 (95%CI: 0.95–0.98, p < 0.001), proving that the questionnaire was reliable in measuring RHIS performances. At univariable level, the following factors were positively associated with good performances: supportive supervision (OR = 3.03 (1.1, 8.3); p = 0.02), receiving feedback from hierarchy (OR = 3.6 (0.99, 13.2); p = 0.05), having received training on health information (OR = 5.0 (1.6, 16.0); p = 0.003), and presence of a performance evaluation plan (OR = 3.3 (1.4, 8.2), p = 0.007). At multivariable level, the only significantly associated factor was having received training on health information (aOR = 3.3 (1.01, 11.1), p = 0.04). Conclusion Training of health staff in the RHIS favors RHIS good performance. Hence, emphasis should be laid on training and empowering staff, frequent and regular RHIS supervision, and frequent and regular feedback, for an efficient RHIS strengthening in Yaoundé.
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Affiliation(s)
- Georges Nguefack-Tsague
- Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon. .,Challenges Initiative Solutions, Yaoundé, Cameroon.
| | - Brian Bongwong Tamfon
- Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon.,Challenges Initiative Solutions, Yaoundé, Cameroon
| | | | - Marie Nicole Ngoufack
- Challenges Initiative Solutions, Yaoundé, Cameroon.,Department of Biochemistry, Faculty of Science, University of Yaoundé 1, Yaoundé, Cameroon.,Systems Biology, Chantal Biya International Reference Centre for Research on HIV and AIDS Prevention and Management (CBIRC), Yaoundé, Cameroon
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9
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Yukich JO, Scott C, Silumbe K, Larson BA, Bennett A, Finn TP, Hamainza B, Conner RO, Porter TR, Keating J, Steketee RW, Eisele TP, Miller JM. Cost-Effectiveness of Focal Mass Drug Administration and Mass Drug Administration with Dihydroartemisinin-Piperaquine for Malaria Prevention in Southern Province, Zambia: Results of a Community-Randomized Controlled Trial. Am J Trop Med Hyg 2020; 103:46-53. [PMID: 32618249 PMCID: PMC7416981 DOI: 10.4269/ajtmh.19-0661] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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] [Indexed: 01/08/2023] Open
Abstract
Community-wide administration of antimalarial drugs in therapeutic doses is a potential tool to prevent malaria infection and reduce the malaria parasite reservoir. To measure the effectiveness and cost of using the antimalarial drug combination dihydroartemisinin–piperaquine (DHAp) through different community-wide distribution strategies, Zambia’s National Malaria Control Centre conducted a three-armed community-randomized controlled trial. The trial arms were as follows: 1) standard of care (SoC) malaria interventions, 2) SoC plus focal mass drug administration (fMDA), and 3) SoC plus MDA. Mass drug administration consisted of offering all eligible individuals DHAP, irrespective of a rapid diagnostic test (RDT) result. Focal mass drug administration consisted of offering DHAP to all eligible individuals who resided in a household where anyone tested positive by RDT. Results indicate that the costs of fMDA and MDA per person targeted and reached are similar (US$9.01 versus US$8.49 per person, respectively, P = 0.87), but that MDA was superior in all cost-effectiveness measures, including cost per infection averted, cost per case averted, cost per death averted, and cost per disability-adjusted life year averted. Subsequent costing of the MDA intervention in a non-trial, operational setting yielded significantly lower costs per person reached (US$2.90). Mass drug administration with DHAp also met the WHO thresholds for “cost-effective interventions” in the Zambian setting in 90% of simulations conducted using a probabilistic sensitivity analysis based on trial costs, whereas fMDA met these criteria in approximately 50% of simulations. A sensitivity analysis using costs from operational deployment and trial effectiveness yielded improved cost-effectiveness estimates. Mass drug administration may be a cost-effective intervention in the Zambian context and can help reduce the parasite reservoir substantially. Mass drug administration was more cost-effective in relatively higher transmission settings. In all scenarios examined, the cost-effectiveness of MDA was superior to that of fMDA.
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Affiliation(s)
- Joshua O Yukich
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Callie Scott
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Seattle, Washington
| | | | - Bruce A Larson
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California
| | - Timothy P Finn
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Busiku Hamainza
- National Malaria Control Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Ruben O Conner
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Seattle, Washington
| | - Travis R Porter
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Joseph Keating
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Richard W Steketee
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Seattle, Washington
| | - Thomas P Eisele
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
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Arambepola R, Keddie SH, Collins EL, Twohig KA, Amratia P, Bertozzi-Villa A, Chestnutt EG, Harris J, Millar J, Rozier J, Rumisha SF, Symons TL, Vargas-Ruiz C, Andriamananjara M, Rabeherisoa S, Ratsimbasoa AC, Howes RE, Weiss DJ, Gething PW, Cameron E. Spatiotemporal mapping of malaria prevalence in Madagascar using routine surveillance and health survey data. Sci Rep 2020; 10:18129. [PMID: 33093622 PMCID: PMC7581764 DOI: 10.1038/s41598-020-75189-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [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: 08/25/2020] [Accepted: 10/12/2020] [Indexed: 11/16/2022] Open
Abstract
Malaria transmission in Madagascar is highly heterogeneous, exhibiting spatial, seasonal and long-term trends. Previous efforts to map malaria risk in Madagascar used prevalence data from Malaria Indicator Surveys. These cross-sectional surveys, conducted during the high transmission season most recently in 2013 and 2016, provide nationally representative prevalence data but cover relatively short time frames. Conversely, monthly case data are collected at health facilities but suffer from biases, including incomplete reporting and low rates of treatment seeking. We combined survey and case data to make monthly maps of prevalence between 2013 and 2016. Health facility catchment populations were estimated to produce incidence rates from the case data. Smoothed incidence surfaces, environmental and socioeconomic covariates, and survey data informed a Bayesian prevalence model, in which a flexible incidence-to-prevalence relationship was learned. Modelled spatial trends were consistent over time, with highest prevalence in the coastal regions and low prevalence in the highlands and desert south. Prevalence was lowest in 2014 and peaked in 2015 and seasonality was widely observed, including in some lower transmission regions. These trends highlight the utility of monthly prevalence estimates over the four year period. By combining survey and case data using this two-step modelling approach, we were able to take advantage of the relative strengths of each metric while accounting for potential bias in the case data. Similar modelling approaches combining large datasets of different malaria metrics may be applicable across sub-Saharan Africa.
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Affiliation(s)
- Rohan Arambepola
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Suzanne H Keddie
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
| | - Emma L Collins
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Katherine A Twohig
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Punam Amratia
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Amelia Bertozzi-Villa
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Institute for Disease Modeling, Bellevue, WA, USA
| | - Elisabeth G Chestnutt
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Joseph Harris
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
| | - Justin Millar
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Jennifer Rozier
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
| | - Susan F Rumisha
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Tasmin L Symons
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Camilo Vargas-Ruiz
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Mauricette Andriamananjara
- Programme National de Lutte contre le Paludisme, Antananarivo, Madagascar
- Ministère de Santé Publique, Antananarivo, Madagascar
| | - Saraha Rabeherisoa
- Programme National de Lutte contre le Paludisme, Antananarivo, Madagascar
| | - Arsène C Ratsimbasoa
- Programme National de Lutte contre le Paludisme, Antananarivo, Madagascar
- University of Fianarantsoa, Fianarantsoa, Madagascar
| | - Rosalind E Howes
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Foundation for Innovative New Diagnostics, Geneva, Switzerland
| | - Daniel J Weiss
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
- Curtin University, Perth, Australia
| | - Peter W Gething
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
- Curtin University, Perth, Australia
| | - Ewan Cameron
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
- Curtin University, Perth, Australia
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11
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Watson-Grant S, Sutherland EG, Xiong K, Thomas JC. Beyond convenience: practical considerations with using routine health data for evaluations. Perspect Public Health 2020; 141:129-130. [PMID: 33000684 PMCID: PMC8142118 DOI: 10.1177/1757913920944196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- S Watson-Grant
- MEASURE Evaluation, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC 27516, USA
| | - E G Sutherland
- MEASURE Evaluation, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC, USA
| | - K Xiong
- MEASURE Evaluation, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC, USA
| | - J C Thomas
- MEASURE Evaluation, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC, USA
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12
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Hung YW, Hoxha K, Irwin BR, Law MR, Grépin KA. Using routine health information data for research in low- and middle-income countries: a systematic review. BMC Health Serv Res 2020; 20:790. [PMID: 32843033 PMCID: PMC7446185 DOI: 10.1186/s12913-020-05660-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [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: 04/18/2020] [Accepted: 08/16/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years, and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications. METHODS Using terms 'routine health information system', 'health information system', or 'health management information system' and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 202,019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form. RESULTS We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last 5 years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored. CONCLUSIONS Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems.
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Affiliation(s)
- Yuen W Hung
- University of Waterloo, School of Public Health and Health Systems, Waterloo, Canada
| | - Klesta Hoxha
- University of Waterloo, School of Public Health and Health Systems, Waterloo, Canada
| | - Bridget R Irwin
- Department of Health Sciences, Wilfrid Laurier University, Waterloo, Canada
| | - Michael R Law
- Centre for Health Services and Policy Research, The University of British Columbia, Vancouver, Canada
| | - Karen A Grépin
- School of Public Health, Hong Kong University, Pok Fu Lam, Hong Kong.
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Abstract
BACKGROUND The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented. CONCLUSION Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.
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Affiliation(s)
- Victor A Alegana
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box 43640, Nairobi, 00100, Kenya.
- Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK.
- Faculty of Science and Technology, Lancaster University, Lancaster, LAI 4YW, UK.
| | - Emelda A Okiro
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box 43640, Nairobi, 00100, Kenya
| | - Robert W Snow
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box 43640, Nairobi, 00100, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7LJ, UK
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14
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Thawer SG, Chacky F, Runge M, Reaves E, Mandike R, Lazaro S, Mkude S, Rumisha SF, Kumalija C, Lengeler C, Mohamed A, Pothin E, Snow RW, Molteni F. Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data. Malar J 2020; 19:177. [PMID: 32384923 PMCID: PMC7206674 DOI: 10.1186/s12936-020-03250-4] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [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: 03/03/2020] [Accepted: 04/29/2020] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Recent malaria control efforts in mainland Tanzania have led to progressive changes in the prevalence of malaria infection in children, from 18.1% (2008) to 7.3% (2017). As the landscape of malaria transmission changes, a sub-national stratification becomes crucial for optimized cost-effective implementation of interventions. This paper describes the processes, data and outputs of the approach used to produce a simplified, pragmatic malaria risk stratification of 184 councils in mainland Tanzania. METHODS Assemblies of annual parasite incidence and fever test positivity rate for the period 2016-2017 as well as confirmed malaria incidence and malaria positivity in pregnant women for the period 2015-2017 were obtained from routine district health information software. In addition, parasite prevalence in school children (PfPR5to16) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014-2015 and 2017. The PfPR5to16 served as a guide to set appropriate cut-offs for the other indicators. For each indicator, the maximum value from the past 3 years was used to allocate councils to one of four risk groups: very low (< 1%PfPR5to16), low (1- < 5%PfPR5to16), moderate (5- < 30%PfPR5to16) and high (≥ 30%PfPR5to16). Scores were assigned to each risk group per indicator per council and the total score was used to determine the overall risk strata of all councils. RESULTS Out of 184 councils, 28 were in the very low stratum (12% of the population), 34 in the low stratum (28% of population), 49 in the moderate stratum (23% of population) and 73 in the high stratum (37% of population). Geographically, most of the councils in the low and very low strata were situated in the central corridor running from the north-east to south-west parts of the country, whilst the areas in the moderate to high strata were situated in the north-west and south-east regions. CONCLUSION A stratification approach based on multiple routine and survey malaria information was developed. This pragmatic approach can be rapidly reproduced without the use of sophisticated statistical methods, hence, lies within the scope of national malaria programmes across Africa.
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Affiliation(s)
- Sumaiyya G Thawer
- Swiss Tropical and Public Health Institute, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Frank Chacky
- Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Manuela Runge
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Erik Reaves
- Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, and US President's Malaria Initiative, Dar es Salaam, United Republic of Tanzania
| | - Renata Mandike
- Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Samwel Lazaro
- Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Sigsbert Mkude
- Swiss Tropical and Public Health Institute, Basel, Switzerland
| | - Susan F Rumisha
- National Institute for Medical Research, Dar es Salaam, Tanzania
| | - Claud Kumalija
- Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
| | - Christian Lengeler
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Ally Mohamed
- Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
- National Malaria Control Programme, Dodoma, Tanzania
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Clinton Health Access Initiative, New York, USA
| | - Robert W Snow
- KEMRI-Welcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Fabrizio Molteni
- Swiss Tropical and Public Health Institute, Basel, Switzerland.
- National Malaria Control Programme, Dodoma, Tanzania.
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15
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Kamau A, Mogeni P, Okiro EA, Snow RW, Bejon P. A systematic review of changing malaria disease burden in sub-Saharan Africa since 2000: comparing model predictions and empirical observations. BMC Med 2020; 18:94. [PMID: 32345315 PMCID: PMC7189714 DOI: 10.1186/s12916-020-01559-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 03/16/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The most widely used measures of declining burden of malaria across sub-Saharan Africa are predictions from geospatial models. These models apply spatiotemporal autocorrelations and covariates to parasite prevalence data and then use a function of parasite prevalence to predict clinical malaria incidence. We attempted to assess whether trends in malaria cases, based on local surveillance, were similar to those captured by Malaria Atlas Project (MAP) incidence surfaces. METHODS We undertook a systematic review (PROSPERO International Prospective Register of Systematic Reviews; ID = CRD42019116834) to identify empirical data on clinical malaria in Africa since 2000, where reports covered at least 5 continuous years. The trends in empirical data were then compared with the trends of time-space matched clinical malaria incidence from MAP using the Spearman rank correlation. The correlations (rho) between changes in empirically observed and modelled estimates of clinical malaria were displayed by forest plots and examined by meta-regression. RESULTS Sixty-seven articles met our inclusion criteria representing 124 sites from 24 African countries. The single most important factor explaining the correlation between empirical observations and modelled predictions was the slope of empirically observed data over time (rho = - 0.989; 95% CI - 0.998, - 0.939; p < 0.001), i.e. steeper declines were associated with a stronger correlation between empirical observations and modelled predictions. Factors such as quality of study, reported measure of malaria and endemicity were only slightly predictive of such correlations. CONCLUSIONS In many locations, both local surveillance data and modelled estimates showed declines in malaria burden and hence similar trends. However, there was a weak association between individual surveillance datasets and the modelled predictions where stalling in progress or resurgence of malaria burden was empirically observed. Surveillance data were patchy, indicating a need for improved surveillance to strengthen both empiric reporting and modelled predictions.
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Affiliation(s)
- Alice Kamau
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya. .,Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
| | | | | | - Robert W Snow
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.,Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Philip Bejon
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.,Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
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Ashton RA, Prosnitz D, Andrada A, Herrera S, Yé Y. Evaluating malaria programmes in moderate- and low-transmission settings: practical ways to generate robust evidence. Malar J 2020; 19:75. [PMID: 32070357 PMCID: PMC7027277 DOI: 10.1186/s12936-020-03158-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [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: 12/05/2019] [Accepted: 02/09/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Many countries have made substantial progress in scaling-up and sustaining malaria intervention coverage, leading to more focalized and heterogeneous transmission in many settings. Evaluation provides valuable information for programmes to understand if interventions have been implemented as planned and with quality, if the programme had the intended impact on malaria burden, and to guide programmatic decision-making. Low-, moderate-, and heterogeneous-transmission settings present unique evaluation challenges because of dynamic and targeted intervention strategies. This paper provides illustration of evaluation approaches and methodologies for these transmission settings, and suggests how to answer evaluation questions specific to the local context. METHODS The Roll Back Malaria Monitoring and Evaluation Reference Group formed a task force in October 2017 to lead development of this framework. The task force includes representatives from National Malaria Programmes, funding agencies, and malaria research and implementing partners. The framework builds on existing guidance for process and outcome evaluations and impact evaluations specifically in high transmission settings. RESULTS The theory of change describes how evaluation questions asked by national malaria programmes in different contexts influence evaluation design. The transmission setting, existing stratification, and data quality and availability are also key considerations. The framework is intended for adaption by countries to their local context, and use for evaluation at sub-national level. Confirmed malaria incidence is recommended as the primary impact indicator due to its sensitivity to detect changes in low-transmission settings. It is expected that process evaluations provide sufficient evidence for programme monitoring and improvement, while impact evaluations are needed following adoption of new mixes of interventions, operational strategies, tools or policies, particularly in contexts of changing malaria epidemiology. Impact evaluations in low-, moderate-, or heterogeneous-transmission settings will likely use plausibility designs, and methods highlighted by the framework include interrupted time series, district-level dose-response analyses, and constructed control methods. Triangulating multiple data sources and analyses is important to strengthen the plausibility argument. CONCLUSIONS This framework provides a structure to assist national malaria programmes and partners to design evaluations in low-, moderate- or heterogeneous-transmission settings. Emphasizing a continuous cycle along the causal pathway linking process evaluation to impact evaluation and then programmatic decision-making, the framework provides practical guidance in evaluation design, analysis, and interpretation to ensure that the evaluation meets national malaria programme priority questions and guides decision-making at national and sub-national levels.
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Affiliation(s)
- Ruth A Ashton
- MEASURE Evaluation, Center for Applied Malaria Research and Evaluation, Tulane School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2300, New Orleans, LA, USA.
| | | | | | - Samantha Herrera
- MEASURE Evaluation, ICF, Rockville, MD, USA.,Save the Children, Washington, DC, USA
| | - Yazoumé Yé
- MEASURE Evaluation, ICF, Rockville, MD, USA
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17
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Alegana VA, Khazenzi C, Akech SO, Snow RW. Estimating hospital catchments from in-patient admission records: a spatial statistical approach applied to malaria. Sci Rep 2020; 10:1324. [PMID: 31992809 PMCID: PMC6987150 DOI: 10.1038/s41598-020-58284-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [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: 10/14/2019] [Accepted: 01/07/2020] [Indexed: 01/20/2023] Open
Abstract
Admission records are seldom used in sub-Saharan Africa to delineate hospital catchments for the spatial description of hospitalised disease events. We set out to investigate spatial hospital accessibility for severe malarial anaemia (SMA) and cerebral malaria (CM). Malaria admissions for children between 1 month and 14 years old were identified from prospective clinical surveillance data recorded routinely at four referral hospitals covering two complete years between December 2015 to November 2016 and November 2017 to October 2018. These were linked to census enumeration areas (EAs) with an age-structured population. A novel mathematical-statistical framework that included EAs with zero observations was used to predict hospital catchment for malaria admissions adjusting for spatial distance. From 5766 malaria admissions, 5486 (95.14%) were linked to specific EA address, of which 272 (5%) were classified as cerebral malaria while 1001 (10%) were severe malaria anaemia. Further, results suggest a marked geographic catchment of malaria admission around the four sentinel hospitals although the extent varied. The relative rate-ratio of hospitalisation was highest at <1-hour travel time for SMA and CM although this was lower outside the predicted hospital catchments. Delineation of catchments is important for planning emergency care delivery and in the use of hospital data to define epidemiological disease burdens. Further hospital and community-based studies on treatment-seeking pathways to hospitals for severe disease would improve our understanding of catchments.
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Affiliation(s)
- Victor A Alegana
- Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box, 43640-00100, Nairobi, Kenya.
- Geography and Environmental Science, University of Southampton, SO17 1BJ, Southampton, UK.
- Faculty of Science and Technology, Lancaster University, LA1 4YR, Lancaster, UK.
| | - Cynthia Khazenzi
- Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box, 43640-00100, Nairobi, Kenya
| | - Samuel O Akech
- Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box, 43640-00100, Nairobi, Kenya
| | - Robert W Snow
- Kenya Medical Research Institute - Wellcome Trust Research Programme, P.O. Box, 43640-00100, Nairobi, Kenya
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, OX3 7LJ, Oxford, UK
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Ouédraogo M, Rouamba T, Samadoulougou S, Kirakoya-Samadoulougou F. Effect of Free Healthcare Policy for Children under Five Years Old on the Incidence of Reported Malaria Cases in Burkina Faso by Bayesian Modelling: "Not only the Ears but also the Head of the Hippopotamus". Int J Environ Res Public Health 2020; 17:E417. [PMID: 31936308 DOI: 10.3390/ijerph17020417] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 12/24/2019] [Accepted: 01/03/2020] [Indexed: 02/02/2023]
Abstract
Burkina Faso has recently implemented an additional strategy, the free healthcare policy, to further improve maternal and child health. This policy targets children under five who bear the brunt of the malaria scourge. The effects of the free-of-charge healthcare were previously assessed in women but not in children. The present study aims at filling this gap by assessing the effect of this policy in children under five with a focus on the induced spatial and temporal changes in malaria morbidity. We used a Bayesian spatiotemporal negative binomial model to investigate the space–time variation in malaria incidence in relation to the implementation of the policy. The analysis relied on malaria routine surveillance data extracted from the national health data repository and spanning the period from January 2013 to December 2018. The model was adjusted for meteorological and contextual confounders. We found that the number of presumed and confirmed malaria cases per 1000 children per month increased between 2013 and 2018. We further found that the implementation of the free healthcare policy was significantly associated with a two-fold increase in the number of tested and confirmed malaria cases compared with the period before the policy rollout. This effect was, however, heterogeneous across the health districts. We attributed the rise in malaria incidence following the policy rollout to an increased use of health services combined with an increased availability of rapid tests and a higher compliance to the “test and treat” policy. The observed heterogeneity in the policy effect was attributed to parallel control interventions, some of which were rolled out at different paces and scales. Our findings call for a sustained and reinforced effort to test all suspected cases so that, alongside an improved case treatment, the true picture of the malaria scourge in children under five emerges clearly (see the hippopotamus almost entirely).
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Stresman G, Bousema T, Cook J. Malaria Hotspots: Is There Epidemiological Evidence for Fine-Scale Spatial Targeting of Interventions? Trends Parasitol 2019; 35:822-834. [PMID: 31474558 DOI: 10.1016/j.pt.2019.07.013] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 07/29/2019] [Accepted: 07/29/2019] [Indexed: 12/20/2022]
Abstract
As data at progressively granular spatial scales become available, the temptation is to target interventions to areas with higher malaria transmission - so-called hotspots - with the aim of reducing transmission in the wider community. This paper reviews literature to determine if hotspots are an intrinsic feature of malaria epidemiology and whether current evidence supports hotspot-targeted interventions. Hotspots are a consistent feature of malaria transmission at all endemicities. The smallest spatial unit capable of supporting transmission is the household, where peri-domestic transmission occurs. Whilst the value of focusing interventions to high-burden areas is evident, there is currently limited evidence that local-scale hotspots fuel transmission. As boundaries are often uncertain, there is no conclusive evidence that hotspot-targeted interventions accelerate malaria elimination.
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Affiliation(s)
- Gillian Stresman
- Infection Biology Department, London School of Hygiene and Tropical Medicine, London, UK.
| | - Teun Bousema
- Radboud University Medical Centre, Department of Microbiology, HB Nijmegen, The Netherlands.
| | - Jackie Cook
- Medical Research Council (MRC) Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine, London, UK
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Lechthaler F, Matthys B, Lechthaler-Felber G, Likwela JL, Mavoko HM, Rika JM, Mutombo MM, Ruckstuhl L, Barczyk J, Shargie E, Prytherch H, Lengeler C. Trends in reported malaria cases and the effects of malaria control in the Democratic Republic of the Congo. PLoS One 2019; 14:e0219853. [PMID: 31344062 PMCID: PMC6658057 DOI: 10.1371/journal.pone.0219853] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [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: 01/29/2019] [Accepted: 07/02/2019] [Indexed: 12/05/2022] Open
Abstract
Background Considerable upscaling of malaria control efforts have taken place over the last 15 years in the Democratic Republic of Congo, the country with the second highest malaria case load after Nigeria. Malaria control interventions have been strengthened in line with the Millenium Development Goals. We analysed the effects of these interventions on malaria cases at health facility level, using a retrospective trend analysis of malaria cases between 2005 and 2014. Data were collected from outpatient and laboratory registers based on a sample of 175 health facilities that represents all eco-epidemiological malaria settings across the country. Methods We applied a time series analysis to assess trends of suspected and confirmed malaria cases, by health province and for different age groups. A linear panel regression model controlled for non-malaria outpatient cases, rain fall, nightlight intensity, health province and time fixed effects, was used to examine the relationship between the interventions and malaria case occurrences, as well as test positivity rates. Results Overall, recorded suspected and confirmed malaria cases in the DRC have increased. The sharp increase in confirmed cases from 2010 coincides with the introduction of the new treatment policy and the resulting scale-up of diagnostic testing. Controlling for confounding factors, the introduction of rapid diagnostic tests (RDTs) was significantly associated with the number of tested and confirmed cases. The test positivity rate fluctuated around 40% without showing any trend. Conclusion The sharp increase in confirmed malaria cases from 2010 is unlikely to be due to a resurgence of malaria, but is clearly associated with improved diagnostic availability, mainly the introduction of RDTs. Before that, a great part of malaria cases were treated based on clinical suspicion. This finding points to a better detection of cases that potentially contributed to improved case management. Furthermore, the expansion of diagnostic testing along with the increase in confirmed cases implies that before 2010, cases were underreported, and that the accuracy of routine data to describe malaria incidence has improved.
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Affiliation(s)
- Filippo Lechthaler
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Basel, Canton of Basel Stadt, Switzerland
- University of Basel, Basel, Canton of Basel Stadt, Switzerland
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, Zollikofen, Canton of Bern, Switzerland
| | - Barbara Matthys
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Basel, Canton of Basel Stadt, Switzerland
- University of Basel, Basel, Canton of Basel Stadt, Switzerland
- * E-mail:
| | - Giulia Lechthaler-Felber
- Faculty of Business and Economics, University of Basel, Basel, Canton of Basel Stadt, Switzerland
| | - Joris Losimba Likwela
- Soins de Santé en Milieu Rural (non-profit organization SANRU), Kinshasa, Democratic Republic of the Congo
| | - Hypolite Muhindo Mavoko
- Tropical Medicine Department, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Junior Matangila Rika
- Tropical Medicine Department, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
| | - Meschac Mutombo Mutombo
- National Malaria Control Program, Ministry of Health, Kinshasa, Democratic Republic of the Congo
| | - Laura Ruckstuhl
- University of Basel, Basel, Canton of Basel Stadt, Switzerland
- Epidemiology and Public Health Department, Swiss Tropical and Public Health Institute, Basel, Canton of Basel Stadt, Switzerland
| | - Joanna Barczyk
- The Global Fund to fight AIDS, Tuberculosis, and Malaria, Geneva, Canton of Geneva, Switzerland
| | - Estifanos Shargie
- The Global Fund to fight AIDS, Tuberculosis, and Malaria, Geneva, Canton of Geneva, Switzerland
| | - Helen Prytherch
- Swiss Centre for International Health, Swiss Tropical and Public Health Institute, Basel, Canton of Basel Stadt, Switzerland
- University of Basel, Basel, Canton of Basel Stadt, Switzerland
| | - Christian Lengeler
- University of Basel, Basel, Canton of Basel Stadt, Switzerland
- Epidemiology and Public Health Department, Swiss Tropical and Public Health Institute, Basel, Canton of Basel Stadt, Switzerland
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Ashton RA, Bennett A, Al-Mafazy AW, Abass AK, Msellem MI, McElroy P, Kachur SP, Ali AS, Yukich J, Eisele TP, Bhattarai A. Use of Routine Health Information System Data to Evaluate Impact of Malaria Control Interventions in Zanzibar, Tanzania from 2000 to 2015. EClinicalMedicine 2019; 12:11-19. [PMID: 31388659 PMCID: PMC6677660 DOI: 10.1016/j.eclinm.2019.05.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 03/27/2019] [Accepted: 05/28/2019] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Impact evaluations allow countries to assess public health gains achieved through malaria investments. This study uses routine health management information system (HMIS) data from Zanzibar to describe changes in confirmed malaria incidence and impact of case management and vector control interventions during 2000-2015. METHODS HMIS data from 129 (82%) public outpatient facilities were analyzed using interrupted time series models to estimate the impact of artemisinin-based combination therapy (ACT), indoor residual spray, and long-lasting insecticidal nets. Evaluation periods were defined as pre-intervention (January 2000 to August 2003), ACT-only (September 2003 to December 2005) and ACT plus vector control (2006-2015). FINDINGS After accounting for climate, seasonality, diagnostic testing rates, and outpatient attendance, average monthly incidence of confirmed malaria showed no trend over the pre-intervention period 2000-2003 (incidence rate ratio (IRR) 0.998, 95% CI 0.995-1.000). During the ACT-only period (2003-2005), the average monthly malaria incidence rate declined compared to the pre-intervention period, showing an overall declining trend during the ACT-only period (IRR 0.984, 95% CI 0.978-0.990). There was no intercept change at the start of the ACT-only period (IRR 1.081, 95% CI 0.968-1.208), but a drop in intercept was identified at the start of the ACT plus vector control period (IRR 0.683, 95% CI 0.597-0.780). During the ACT plus vector control period (2006-2015), the rate of decline in average monthly malaria incidence slowed compared to the ACT-only period, but the incidence rate continued to show an overall slight declining trend during 2006-2015 (IRR 0.993, 95% CI 0.992-0.994). INTERPRETATION This study presents a rigorous approach to the use of HMIS data in evaluating the impact of malaria control interventions. Evidence is presented for a rapid decline in malaria incidence during the period of ACT roll out compared to pre-intervention, with a rapid drop in malaria incidence following introduction of vector control and a slower declining incidence trend thereafter.
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Affiliation(s)
- Ruth A. Ashton
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Corresponding author at: School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2300, New Orleans, LA, USA.
| | - Adam Bennett
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, CA, USA
| | - Abdul-Wahid Al-Mafazy
- Zanzibar Malaria Elimination Programme, Ministry of Health, Zanzibar, United Republic of Tanzania
| | - Ali K. Abass
- Zanzibar Malaria Elimination Programme, Ministry of Health, Zanzibar, United Republic of Tanzania
| | | | - Peter McElroy
- U.S. President's Malaria Initiative, Malaria Branch, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - S. Patrick Kachur
- Malaria Branch, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
- Mailman School of Public Health, Columbia University, NY, New York, USA
| | - Abdullah S. Ali
- Zanzibar Malaria Elimination Programme, Ministry of Health, Zanzibar, United Republic of Tanzania
| | - Joshua Yukich
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Thomas P. Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Achuyt Bhattarai
- U.S. President's Malaria Initiative, Malaria Branch, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
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Ng M, Ellicott Colson K, Fullman N, Dwyer-Lindgren L, Achoki T, Schneider MT, Mulenga P, Hangoma P, Masiye F, Gakidou E. Assessing the Contribution of Malaria Vector Control and Other Maternal and Child Health Interventions in Reducing All-Cause Under-Five Mortality in Zambia, 1990-2010. Am J Trop Med Hyg 2019; 97:58-64. [PMID: 26880778 PMCID: PMC5619928 DOI: 10.4269/ajtmh.15-0315] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [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] [Indexed: 11/16/2022] Open
Abstract
Under-five mortality in Zambia has declined since 1990, with reductions accelerating after 2000. Zambia’s scale-up of malaria control is viewed as the driver of these gains, but past studies have not fully accounted for other potential factors. This study sought to systematically evaluate the impact of malaria vector control on under-five mortality. Using a mixed-effects regression model, we quantified the relationship between malaria vector control, other priority health interventions, and socioeconomic indicators and district-level under-five mortality trends from 1990 to 2010. We then conducted counterfactual analyses to estimate under-five mortality in the absence of scaling up malaria vector control. Throughout Zambia, increased malaria vector control coverage coincided with scaling up three other interventions: the pentavalent vaccine, exclusive breast-feeding, and prevention of mother-to-child transmission of HIV services. This simultaneous scale-up made statistically isolating intervention-specific impact infeasible. Instead, in combination, these interventions jointly accelerated declines in under-five mortality by 11% between 2000 and 2010. Zambia’s scale-up of multiple interventions is notable, yet our findings highlight challenges in quantifying program-specific impact without better health data and information systems. As countries aim to further improve health outcomes, there is even greater need—and opportunity—to strengthen routine data systems and to develop more rigorous evaluation strategies.
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Affiliation(s)
- Marie Ng
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington
| | | | - Nancy Fullman
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington
| | - Laura Dwyer-Lindgren
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington
| | - Tom Achoki
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington
| | - Matthew T Schneider
- United States Agency for International Development, Washington, District of Columbia
| | | | - Peter Hangoma
- Department of Economics, University of Bergen, Bergen, Norway.,School of Humanities and Social Sciences, University of Zambia, Lusaka, Zambia
| | - Felix Masiye
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington.,School of Humanities and Social Sciences, University of Zambia, Lusaka, Zambia
| | - Emmanuela Gakidou
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington
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Juran S, Broer PN, Klug SJ, Snow RC, Okiro EA, Ouma PO, Snow RW, Tatem AJ, Meara JG, Alegana VA. Geospatial mapping of access to timely essential surgery in sub-Saharan Africa. BMJ Glob Health 2018; 3:e000875. [PMID: 30147944 PMCID: PMC6104751 DOI: 10.1136/bmjgh-2018-000875] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 07/04/2018] [Accepted: 07/06/2018] [Indexed: 11/05/2022] Open
Abstract
INTRODUCTION Despite an estimated one-third of the global burden of disease being surgical, only limited estimates of accessibility to surgical treatment in sub-Saharan Africa exist and these remain spatially undefined. Geographical metrics of access to major hospitals were estimated based on travel time. Estimates were then used to assess need for surgery at country level. METHODS Major district and regional hospitals were assumed to have capability to perform bellwether procedures. Geographical locations of hospitals in relation to the population in the 47 sub-Saharan countries were combined with spatial ancillary data on roads, elevation, land use or land cover to estimate travel-time metrics of 30 min, 1 hour and 2 hours. Hospital catchment was defined as population residing in areas less than 2 hours of travel time to the next major hospital. Travel-time metrics were combined with fine-scale population maps to define burden of surgery at hospital catchment level. RESULTS Overall, the majority of the population (92.5%) in sub-Saharan Africa reside in areas within 2 hours of a major hospital catchment defined based on spatially defined travel times. The burden of surgery in all-age population was 257.8 million to 294.7 million people and was highest in high-population density countries and lowest in sparsely populated or smaller countries. The estimated burden in children <15 years was 115.3 million to 131.8 million and had similar spatial distribution to the all-age pattern. CONCLUSION The study provides an assessment of accessibility and burden of surgical disease in sub-Saharan Africa. Yet given the optimistic assumption of adequare surgical capability of major hospitals, the true burden of surgical disease is expected to be much greater. In-depth health facility assessments are needed to define infrastructure, personnel and medicine supply for delivering timely and safe affordable surgery to further inform the analysis.
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Affiliation(s)
- Sabrina Juran
- United Nations Population Fund, Technical Division, Population and Development Branch, New York City, New York, USA
- Lehrstuhl für Epidemiologie, Technische Universität München, München, Germany
| | - P Niclas Broer
- Klinikum Bogenhausen, Städtisches Klinikum München, Technische Universität München, München, Germany
| | - Stefanie J Klug
- Lehrstuhl für Epidemiologie, Technische Universität München, München, Germany
| | - Rachel C Snow
- United Nations Population Fund, Technical Division, Population and Development Branch, New York City, New York, USA
| | - Emelda A Okiro
- Kenya Medical Research Institute/Wellcome Trust Research Programme, Nairobi, Kenya
| | - Paul O Ouma
- Kenya Medical Research Institute/Wellcome Trust Research Programme, Nairobi, Kenya
| | - Robert W Snow
- Kenya Medical Research Institute/Wellcome Trust Research Programme, Nairobi, Kenya
| | - Andrew J Tatem
- WorldPop, Geography and Environment, University of Southampton, Southampton, UK
- Flowminder Foundation, Stockholm, Sweden
| | - John G Meara
- Program in Global Surgery and Social Change, Harvard Medical School, Boston, Massachusetts, USA
| | - Victor A Alegana
- WorldPop, Geography and Environment, University of Southampton, Southampton, UK
- Flowminder Foundation, Stockholm, Sweden
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Florey LS, Bennett A, Hershey CL, Bhattarai A, Nielsen CF, Ali D, Luhanga M, Taylor C, Eisele TP, Yé Y. Impact of Insecticide-Treated Net Ownership on All-Cause Child Mortality in Malawi, 2006-2010. Am J Trop Med Hyg 2017; 97:65-75. [PMID: 28990922 PMCID: PMC5619930 DOI: 10.4269/ajtmh.15-0929] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [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] [Indexed: 11/07/2022] Open
Abstract
Insecticide-treated nets (ITNs) have been shown to be highly effective at reducing malaria morbidity and mortality in children. However, there are limited studies that assess the association between increasing ITN coverage and child mortality over time, at the national level, and under programmatic conditions. Two analytic approaches were used to examine this association: a retrospective cohort analysis of individual children and a district-level ecologic analysis. To evaluate the association between household ITN ownership and all-cause child mortality (ACCM) at the individual level, data from the 2010 Demographic and Health Survey (DHS) were modeled in a Cox proportional hazards framework while controlling for numerous environmental, household, and individual confounders through the use of exact matching. To evaluate population-level association between ITN ownership and ACCM between 2006 and 2010, program ITN distribution data and mortality data from the 2006 Multiple Indicator Cluster Survey and the 2010 DHS were aggregated at the district level and modeled using negative binomial regression. In the Cox model controlling for household, child and maternal health factors, children between 1 and 59 months in households owning an ITN had significantly lower mortality compared with those without an ITN (hazard ratio = 0.75, 95% confidence interval [CI] = 0.62–90). In the district-level model, higher ITN ownership was significantly associated with lower ACCM (incidence rate ratio = 0.77; 95% CI = 0.60–0.98). These findings suggest that increasing ITN ownership may have contributed to the decline in ACCM during 2006–2010 in Malawi and represent a novel use of district-level data from nationally representative surveys.
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Affiliation(s)
| | - Adam Bennett
- Malaria Elimination Initiative, University of California, San Francisco, California
| | - Christine L Hershey
- President's Malaria Initiative, United States Agency for International Development, Arlington, Virginia
| | - Achuyt Bhattarai
- President's Malaria Initiative, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Carrie F Nielsen
- President's Malaria Initiative, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Doreen Ali
- National Malaria Control Programme, Ministry of Health, Lilongwe, Malawi
| | - Misheck Luhanga
- National Malaria Control Programme, Ministry of Health, Lilongwe, Malawi
| | | | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Yazoume Yé
- ICF, MEASURE Evaluation, Rockville, Maryland
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Yé Y, Eisele TP, Eckert E, Korenromp E, Shah JA, Hershey CL, Ivanovich E, Newby H, Carvajal-Velez L, Lynch M, Komatsu R, Cibulskis RE, Moore Z, Bhattarai A. Framework for Evaluating the Health Impact of the Scale-Up of Malaria Control Interventions on All-Cause Child Mortality in Sub-Saharan Africa. Am J Trop Med Hyg 2017; 97:9-19. [PMID: 28990923 PMCID: PMC5619929 DOI: 10.4269/ajtmh.15-0363] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [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] [Indexed: 11/15/2022] Open
Abstract
Concerted efforts from national and international partners have scaled up malaria control interventions, including insecticide-treated nets, indoor residual spraying, diagnostics, prompt and effective treatment of malaria cases, and intermittent preventive treatment during pregnancy in sub-Saharan Africa (SSA). This scale-up warrants an assessment of its health impact to guide future efforts and investments; however, measuring malaria-specific mortality and the overall impact of malaria control interventions remains challenging. In 2007, Roll Back Malaria's Monitoring and Evaluation Reference Group proposed a theoretical framework for evaluating the impact of full-coverage malaria control interventions on morbidity and mortality in high-burden SSA countries. Recently, several evaluations have contributed new ideas and lessons to strengthen this plausibility design. This paper harnesses that new evaluation experience to expand the framework, with additional features, such as stratification, to examine subgroups most likely to experience improvement if control programs are working; the use of a national platform framework; and analysis of complete birth histories from national household surveys. The refined framework has shown that, despite persisting data challenges, combining multiple sources of data, considering potential contributions from both fundamental and proximate contextual factors, and conducting subnational analyses allows identification of the plausible contributions of malaria control interventions on malaria morbidity and mortality.
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Affiliation(s)
- Yazoume Yé
- MEASURE Evaluation, ICF, Rockville, Maryland
| | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Erin Eckert
- President's Malaria Initiative, Bureau for Global Health, United States Agency for International Development, Washington, District of Columbia
| | - Eline Korenromp
- Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Avenir Health, Geneva, Switzerland
| | - Jui A Shah
- MEASURE Evaluation, ICF, Rockville, Maryland
| | - Christine L Hershey
- President's Malaria Initiative, Bureau for Global Health, United States Agency for International Development, Washington, District of Columbia
| | | | - Holly Newby
- Independent Consultant based on Stockholm, Sweden
| | - Liliana Carvajal-Velez
- Division of Data, Research, and Policy, Data and Analytics Section, United Nations Children's Fund, New York, New York
| | - Michael Lynch
- President's Malaria Initiative, Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Ryuichi Komatsu
- The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland
| | | | | | - Achuyt Bhattarai
- President's Malaria Initiative, Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia
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Abstract
BACKGROUND Increasing coverage of malaria vector control interventions globally has led to significant reductions in disease burden. However due to its high recurrent cost, there is a need to determine if and when vector control can be safely scaled back after transmission has been reduced. METHODS AND FINDINGS A mathematical model of Plasmodium falciparum malaria epidemiology was simulated to determine the impact of scaling back vector control on transmission and disease. A regression analysis of simulation results was conducted to derive predicted probabilities of resurgence, severity of resurgence and time to resurgence under various settings. Results indicate that, in the absence of secular changes in transmission, there are few scenarios where vector control can be removed without high expectation of resurgence. These, potentially safe, scenarios are characterized by low historic entomological inoculation rates, successful vector control programmes that achieve elimination or near elimination, and effective surveillance systems with high coverage and effective treatment of malaria cases. CONCLUSIONS Programmes and funding agencies considering scaling back or withdrawing vector control from previously malaria endemic areas need to first carefully consider current receptivity and other available interventions in a risk assessment. Surveillance for resurgence needs to be continuously conducted over a long period of time in order to ensure a rapid response should vector control be withdrawn.
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Affiliation(s)
- Joshua O. Yukich
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, 1440 Canal St. 8317, New Orleans, LA 70112 USA
| | - Nakul Chitnis
- Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland
- University of Basel, Basel, Switzerland
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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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Ashton RA, Bennett A, Yukich J, Bhattarai A, Keating J, Eisele TP. Methodological Considerations for Use of Routine Health Information System Data to Evaluate Malaria Program Impact in an Era of Declining Malaria Transmission. Am J Trop Med Hyg 2017; 97:46-57. [PMID: 28990915 PMCID: PMC5619932 DOI: 10.4269/ajtmh.16-0734] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 10/24/2016] [Indexed: 12/01/2022] Open
Abstract
Coverage of malaria control interventions is increasing dramatically across endemic countries. Evaluating the impact of malaria control programs and specific interventions on health indicators is essential to enable countries to select the most effective and appropriate combination of tools to accelerate progress or proceed toward malaria elimination. When key malaria interventions have been proven effective under controlled settings, further evaluations of the impact of the intervention using randomized approaches may not be appropriate or ethical. Alternatives to randomized controlled trials are therefore required for rigorous evaluation under conditions of routine program delivery. Routine health management information system (HMIS) data are a potentially rich source of data for impact evaluation, but have been underused in impact evaluation due to concerns over internal validity, completeness, and potential bias in estimates of program or intervention impact. A range of methodologies were identified that have been used for impact evaluations with malaria outcome indicators generated from HMIS data. Methods used to maximize internal validity of HMIS data are presented, together with recommendations on reducing bias in impact estimates. Interrupted time series and dose-response analyses are proposed as the strongest quasi-experimental impact evaluation designs for analysis of malaria outcome indicators from routine HMIS data. Interrupted time series analysis compares the outcome trend and level before and after the introduction of an intervention, set of interventions or program. The dose-response national platform approach explores associations between intervention coverage or program intensity and the outcome at a subnational (district or health facility catchment) level.
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Affiliation(s)
- Ruth A. Ashton
- Center for Applied Malaria Research and Evaluation, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California
| | - Joshua Yukich
- Center for Applied Malaria Research and Evaluation, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Achuyt Bhattarai
- President's Malaria Initiative, Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Joseph Keating
- Center for Applied Malaria Research and Evaluation, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Thomas P. Eisele
- Center for Applied Malaria Research and Evaluation, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
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Rosewell A, Makita L, Muscatello D, John LN, Bieb S, Hutton R, Ramamurthy S, Shearman P. Health information system strengthening and malaria elimination in Papua New Guinea. Malar J 2017; 16:278. [PMID: 28679421 PMCID: PMC5499047 DOI: 10.1186/s12936-017-1910-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [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: 03/26/2017] [Accepted: 06/26/2017] [Indexed: 11/17/2022] Open
Abstract
Background The objective of the study was to describe an m-health initiative to strengthen malaria surveillance in a 184-health facility, multi-province, project aimed at strengthening the National Health Information System (NHIS) in a country with fragmented malaria surveillance, striving towards enhanced control, pre-elimination. Methods A remote-loading mobile application and secure online platform for health professionals was created to interface with the new system (eNHIS). A case-based malaria testing register was developed and integrated geo-coded households, villages and health facilities. A malaria programme management dashboard was created, with village-level malaria mapping tools, and statistical algorithms to identify malaria outbreaks. Results Since its inception in 2015, 160,750 malaria testing records, including village of residence, have been reported to the eNHIS. These case-based, geo-coded malaria data are 100% complete, with a median data entry delay of 9 days from the date of testing. The system maps malaria to the village level in near real-time as well as the availability of treatment and diagnostics to health facility level. Data aggregation, analysis, outbreak detection, and reporting are automated. Conclusions The study demonstrates that using mobile technologies and GIS in the capture and reporting of NHIS data in Papua New Guinea provides timely, high quality, geo-coded, case-based malaria data required for malaria elimination. The health systems strengthening approach of integrating malaria information management into the eNHIS optimizes sustainability and provides enormous flexibility to cater for future malaria programme needs.
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Affiliation(s)
- Alexander Rosewell
- PNG Remote Sensing Centre, PO Box 1733, Waterfront, Konedobu, Port Moresby, Papua New Guinea. .,School of Public Health and Community Medicine, University of New South Wales, Sydney, 2052, Australia.
| | - Leo Makita
- National Department of Health, Port Moresby, Papua New Guinea
| | - David Muscatello
- School of Public Health and Community Medicine, University of New South Wales, Sydney, 2052, Australia
| | | | - Sibauk Bieb
- National Department of Health, Port Moresby, Papua New Guinea
| | | | - Sundar Ramamurthy
- PNG Remote Sensing Centre, PO Box 1733, Waterfront, Konedobu, Port Moresby, Papua New Guinea
| | - Phil Shearman
- PNG Remote Sensing Centre, PO Box 1733, Waterfront, Konedobu, Port Moresby, Papua New Guinea.,School of Botany and Zoology, The Australian National University, Linnaeus Way, Canberra, 0200, Australia
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Bennett A, Yukich J, Miller JM, Keating J, Moonga H, Hamainza B, Kamuliwo M, Andrade-Pacheco R, Vounatsou P, Steketee RW, Eisele TP. The relative contribution of climate variability and vector control coverage to changes in malaria parasite prevalence in Zambia 2006-2012. Parasit Vectors 2016; 9:431. [PMID: 27496161 PMCID: PMC4974721 DOI: 10.1186/s13071-016-1693-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [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: 01/07/2015] [Accepted: 07/11/2016] [Indexed: 12/02/2022] Open
Abstract
Background Four malaria indicator surveys (MIS) were conducted in Zambia between 2006 and 2012 to evaluate malaria control scale-up. Nationally, coverage of insecticide-treated nets (ITNs) and indoor residual spraying (IRS) increased over this period, while parasite prevalence in children 1–59 months decreased dramatically between 2006 and 2008, but then increased from 2008 to 2010. We assessed the relative effects of vector control coverage and climate variability on malaria parasite prevalence over this period. Methods Nationally-representative MISs were conducted in April-June of 2006, 2008, 2010 and 2012 to collect household-level information on malaria control interventions such as IRS, ITN ownership and use, and child parasite prevalence by microscopic examination of blood smears. We fitted Bayesian geostatistical models to assess the association between IRS and ITN coverage and climate variability and malaria parasite prevalence. We created predictions of the spatial distribution of malaria prevalence at each time point and compared results of varying IRS, ITN, and climate inputs to assess their relative contributions to changes in prevalence. Results Nationally, the proportion of households owning an ITN increased from 37.8 % in 2006 to 64.3 % in 2010 and 68.1 % in 2012, with substantial heterogeneity sub-nationally. The population-adjusted predicted child malaria parasite prevalence decreased from 19.6 % in 2006 to 10.4 % in 2008, but rose to 15.3 % in 2010 and 13.5 % in 2012. We estimated that the majority of this prevalence increase at the national level between 2008 and 2010 was due to climate effects on transmission, although there was substantial heterogeneity at the provincial level in the relative contribution of changing climate and ITN availability. We predict that if climate factors preceding the 2010 survey were the same as in 2008, the population-adjusted prevalence would have fallen to 9.9 % nationally. Conclusions These results suggest that a combination of climate factors and reduced intervention coverage in parts of the country contributed to both the reduction and rebound in malaria parasite prevalence. Unusual rainfall patterns, perhaps related to moderate El Niño conditions, may have contributed to this variation. Zambia has demonstrated considerable success in scaling up vector control. This analysis highlights the importance of accounting for climate variability when using cross-sectional data for evaluation of malaria control efforts. Electronic supplementary material The online version of this article (doi:10.1186/s13071-016-1693-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California, 500 16th St, San Francisco, CA, 94158, USA. .,Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
| | - Josh Yukich
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - John M Miller
- PATH Malaria Control and Evaluation Partnership in Africa (MACEPA), Lusaka, Zambia
| | - Joseph Keating
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Hawela Moonga
- National Malaria Control Centre, Ministry of Health, Lusaka, Zambia
| | - Busiku Hamainza
- National Malaria Control Centre, Ministry of Health, Lusaka, Zambia
| | - Mulakwa Kamuliwo
- National Malaria Control Centre, Ministry of Health, Lusaka, Zambia
| | - Ricardo Andrade-Pacheco
- Malaria Elimination Initiative, Global Health Group, University of California, 500 16th St, San Francisco, CA, 94158, USA
| | - Penelope Vounatsou
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Richard W Steketee
- PATH Malaria Control and Evaluation Partnership in Africa (MACEPA), Lusaka, Zambia
| | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
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31
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Sturrock HJW, Bennett AF, Midekisa A, Gosling RD, Gething PW, Greenhouse B. Mapping Malaria Risk in Low Transmission Settings: Challenges and Opportunities. Trends Parasitol 2016; 32:635-45. [PMID: 27238200 DOI: 10.1016/j.pt.2016.05.001] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2016] [Revised: 04/29/2016] [Accepted: 05/02/2016] [Indexed: 11/24/2022]
Abstract
As malaria transmission declines, it becomes increasingly focal and prone to outbreaks. Understanding and predicting patterns of transmission risk becomes an important component of an effective elimination campaign, allowing limited resources for control and elimination to be targeted cost-effectively. Malaria risk mapping in low transmission settings is associated with some unique challenges. This article reviews the main challenges and opportunities related to risk mapping in low transmission areas including recent advancements in risk mapping low transmission malaria, relevant metrics, and statistical approaches and risk mapping in post-elimination settings.
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Larsen DA, Chisha Z, Winters B, Mwanza M, Kamuliwo M, Mbwili C, Hawela M, Hamainza B, Chirwa J, Craig AS, Rutagwera MR, Lungu C, Ngwenya-Kangombe T, Cheelo S, Miller JM, Bridges DJ, Winters AM. Malaria surveillance in low-transmission areas of Zambia using reactive case detection. Malar J 2015; 14:465. [PMID: 26586264 PMCID: PMC4653936 DOI: 10.1186/s12936-015-0895-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [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: 08/04/2015] [Accepted: 09/14/2015] [Indexed: 12/02/2022] Open
Abstract
Background Repeat national
household surveys suggest highly variable malaria transmission and increasing coverage of high-impact malaria interventions throughout Zambia. Many areas of very low malaria transmission, especially across southern and central regions, are driving efforts towards sub-national elimination. Case description Reactive case detection (RCD) is conducted in Southern Province and urban areas of Lusaka in connection with confirmed incident malaria cases presenting to a community health worker (CHW) or clinic and suspected of being the result of local transmission. CHWs travel to the household of the incident malaria case and screen individuals living in adjacent houses in urban Lusaka and within 140 m in Southern Province for malaria infection using a rapid diagnostic test, treating those testing positive with artemether–lumefantrine. Discussion Reactive case detection improves access to health care and increases the capacity for the health system to identify malaria infections. The system is useful for targeting malaria interventions, and was instrumental for guiding focal indoor residual spraying in Lusaka during the 2014/2015 spray season. Variations to maximize impact of the current RCD protocol are being considered, including the use of anti-malarials with a longer lasting, post-treatment prophylaxis. Conclusion The RCD system in Zambia is one example of a malaria elimination surveillance system which has increased access to health care within rural communities while leveraging community members to build malaria surveillance capacity.
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Affiliation(s)
- David A Larsen
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia. .,Department of Public Health, Food Studies and Nutrition, Syracuse University, Syracuse, NY, USA.
| | - Zunda Chisha
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia.
| | - Benjamin Winters
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia. .,University of Montana School of Public and Community Health Sciences, Missoula, MT, USA.
| | - Mercie Mwanza
- National Malaria Control Centre, Ministry of Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Mulakwa Kamuliwo
- National Malaria Control Centre, Ministry of Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Clara Mbwili
- Lusaka Community District Medical Office, Ministry of Community Development Mother and Child Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Moonga Hawela
- National Malaria Control Centre, Ministry of Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Busiku Hamainza
- National Malaria Control Centre, Ministry of Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Jacob Chirwa
- National Malaria Control Centre, Ministry of Health, Government of the Republic of Zambia, Lusaka, Zambia.
| | - Allen S Craig
- Malaria Branch and US President's Malaria Initiative (Currently Global Immunization Division), Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Marie-Reine Rutagwera
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia.
| | - Chris Lungu
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia.
| | | | - Sanford Cheelo
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia.
| | - John M Miller
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia.
| | - Daniel J Bridges
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia.
| | - Anna M Winters
- Akros, Cresta Golfview Grounds, Great East Road, Lusaka, Zambia. .,University of Montana School of Public and Community Health Sciences, Missoula, MT, USA.
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Coker E, Ghosh J, Jerrett M, Gomez-Rubio V, Beckerman B, Cockburn M, Liverani S, Su J, Li A, Kile ML, Ritz B, Molitor J. Modeling spatial effects of PM(2.5) on term low birth weight in Los Angeles County. Environ Res 2015. [PMID: 26196780 DOI: 10.1016/j.envres.2015.06.044] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM2.5) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure-response of PM2.5 on TLBW to be the same throughout a large geographical area. Health effects related to PM2.5 exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure-response relationship between individual-level exposure to PM2.5 and TLBW. Here, we examine the overall and spatially varying exposure-response relationship between PM2.5 and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM2.5 from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM2.5 level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure-response for PM2.5 and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure-response estimates for PM2.5 on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective.
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Affiliation(s)
- Eric Coker
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA.
| | - Jokay Ghosh
- School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Michael Jerrett
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | | | - Bernardo Beckerman
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Myles Cockburn
- Preventive Medicine and Spatial Sciences, University of Southern California, Los Angeles, CA, USA
| | - Silvia Liverani
- Department of Mathematics, Brunel University, London, United Kingdom
| | - Jason Su
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Arthur Li
- Department of Information Science, City of Hope National Cancer Center, Duarte, CA, USA
| | - Molly L Kile
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA
| | - Beate Ritz
- School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - John Molitor
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA
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Silumbe K, Yukich JO, Hamainza B, Bennett A, Earle D, Kamuliwo M, Steketee RW, Eisele TP, Miller JM. Costs and cost-effectiveness of a large-scale mass testing and treatment intervention for malaria in Southern Province, Zambia. Malar J 2015; 14:211. [PMID: 25985992 PMCID: PMC4490652 DOI: 10.1186/s12936-015-0722-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [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: 12/02/2014] [Accepted: 05/05/2015] [Indexed: 11/17/2022] Open
Abstract
Background A cluster, randomized, control trial of three dry-season rounds of a mass testing and treatment intervention (MTAT) using rapid diagnostic tests (RDTs) and artemether-lumefantrine (AL) was conducted in four districts in Southern Province, Zambia. Methods Data were collected on the costs and logistics of the intervention and paired with effectiveness estimated from a community randomized control trial for the purpose of conducting a provider perspective cost-effectiveness analysis of MTAT vs no MTAT (Standard of Care). Results Dry-season MTAT in this setting did not reduce malaria transmission sufficiently to permit transition to a case-investigation strategy to then pursue malaria elimination, however, the intervention did substantially reduce malaria illness and was a highly cost-effective intervention for malaria burden reduction in this moderate transmission area. The cost per RDT administered was estimated to be USD4.39 (range: USD1.62-13.96) while the cost per AL treatment administered was estimated to be USD34.74 (range: USD3.87-3,835). The net cost per disability adjusted life year averted (incremental cost-effectiveness ratio) was estimated to be USD804. Conclusions The intervention appears to be highly cost-effective relative to World Health Organization thresholds for malaria burden reduction in Zambia as compared to no MTAT. However, it was estimated that population-wide mass drug administration is likely to be more cost-effective for burden reduction and for transmission reduction compared to MTAT.
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Affiliation(s)
- Kafula Silumbe
- Malaria Control and Evaluation Partnership in Africa (PATH-MACEPA), Lusaka, Zambia.
| | - Joshua O Yukich
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
| | | | - Adam Bennett
- Malaria Elimination Initiative, University of California San Francisco, San Francisco, USA.
| | - Duncan Earle
- Malaria Control and Evaluation Partnership in Africa (PATH-MACEPA), Lusaka, Zambia.
| | | | - Richard W Steketee
- Malaria Control and Evaluation Partnership in Africa (PATH-MACEPA), Lusaka, Zambia.
| | - Thomas P Eisele
- Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
| | - John M Miller
- Malaria Control and Evaluation Partnership in Africa (PATH-MACEPA), Lusaka, Zambia.
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35
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Weiss DJ, Mappin B, Dalrymple U, Bhatt S, Cameron E, Hay SI, Gething PW. Re-examining environmental correlates of Plasmodium falciparum malaria endemicity: a data-intensive variable selection approach. Malar J 2015; 14:68. [PMID: 25890035 PMCID: PMC4333887 DOI: 10.1186/s12936-015-0574-x] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [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: 11/19/2014] [Accepted: 01/18/2015] [Indexed: 11/14/2022] Open
Abstract
Background Malaria risk maps play an increasingly important role in disease control planning, implementation, and evaluation. The construction of these maps using modern geospatial techniques relies on covariate grids: continuous surfaces quantifying environmental factors that partially explain spatial heterogeneity in malaria endemicity. Although crucial, past variable selection processes for this purpose have often been subjective and ad-hoc, with many covariates used in modeling with little quantitative justification. Methods This research consists of an extensive covariate construction and selection process for predicting Plasmodium falciparum parasite rates (PfPR) in Africa for years 2000-2012. First, a literature review was conducted to establish a comprehensive list of covariates used for malaria mapping. Second, a library of covariate data was assembled to reflect this list, a process that included the construction of multiple, temporally dynamic datasets. Third, the resulting set of covariates was leveraged to create more than 50 million possible covariate terms via factorial combinations of different spatial and temporal aggregations, transformations, and pairwise interactions. Fourth, the expanded set of covariates was reduced via successive selection criteria to yield a robust covariate subset that was assessed using an out-of-sample validation approach. Results The final covariate subset included predominately dynamic covariates and it substantially out-performed earlier sets used by the Malaria Atlas Project (MAP) for creating global malaria risk maps, with the pseudo-R2 value for the out-of-sample validation increasing from 0.43 to 0.52. Dynamic covariates improved the model, with 17 of the 20 new covariates consisting of monthly or annual products, but the selected covariates were typically interaction terms that included both dynamic and synoptic datasets. Thus the interplay between normal (i.e., long-term averages) and immediate conditions may be key for characterizing environmental controls on parasite rate. Conclusions This analysis represents the first effort to systematically audit covariate utility for malaria mapping and then derive an objective, empirically based set of environmental covariates for modeling PfPR. The new covariates produce more reliable representations of malaria risk patterns and how they are changing through time, and these covariates will be used to characterize spatially and temporally varying environmental conditions affecting PfPR within a geostatistical-modeling framework, thus building upon previous research by MAP that produced global malaria maps for 2007 and 2010. Electronic supplementary material The online version of this article (doi:10.1186/s12936-015-0574-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Daniel J Weiss
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
| | - Bonnie Mappin
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
| | - Ursula Dalrymple
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
| | - Samir Bhatt
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
| | - Ewan Cameron
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
| | - Simon I Hay
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK. .,Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
| | - Peter W Gething
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, Oxford, UK.
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