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Joseph NK, Macharia PM, Okiro EA. Progress towards achieving child survival goals in Kenya after devolution: Geospatial analysis with scenario-based projections, 2015-2025. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000686. [PMID: 36962627 PMCID: PMC10021401 DOI: 10.1371/journal.pgph.0000686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 09/07/2022] [Indexed: 06/18/2023]
Abstract
Subnational projections of under-5 mortality (U5M) have increasingly become an essential planning tool to support Sustainable Development Goals (SDGs) agenda and strategies for improving child survival. To support child health policy, planning, and tracking child development goals in Kenya, we projected U5M at units of health decision making. County-specific annual U5M were estimated using a multivariable Bayesian space-time hierarchical model based on intervention coverage from four alternate intervention scale-up scenarios assuming 1) the highest subnational intervention coverage in 2014, 2) projected coverage based on the fastest county-specific rate of change observed in the period between 2003-2014 for each intervention, 3) the projected national coverage based on 2003-2014 trends and 4) the country-specific targets of intervention coverage relative to business as usual (BAU) scenario. We compared the percentage change in U5M based on the four scale-up scenarios relative to BAU and examined the likelihood of reaching SDG 3.2 target of at least 25 deaths/1,000 livebirths by 2022 and 2025. Projections based on 10 factors assuming BAU, showed marginal reductions in U5M across counties with all the counties except Mandera county not achieving the SDG 3.2 target by 2025. Further, substantial reductions in U5M would be achieved based on the various intervention scale-up scenarios, with 63.8% (30), 74.5% (35), 46.8% (22) and 61.7% (29) counties achieving SDG target for scenarios 1,2,3 and 4 respectively by 2025. Scenario 2 yielded the highest reductions of U5M with individual scale-up of access to improved water, recommended treatment of fever and accelerated HIV prevalence reduction showing considerable impact on U5M reduction (≥ 20%) relative to BAU. Our results indicate that sustaining an ambitious intervention scale-up strategy matching the fastest rate observed between 2003-2014 would substantially reduce U5M in Kenya. However, despite this ambitious scale-up scenario, 25% (12 of 47) of the Kenya's counties would still not achieve SDG 3.2 target by 2025.
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Affiliation(s)
- Noel K. Joseph
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - 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
| | - Emelda A. Okiro
- 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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Runge M, Thawer SG, Molteni F, Chacky F, Mkude S, Mandike R, Snow RW, Lengeler C, Mohamed A, Pothin E. Sub-national tailoring of malaria interventions in Mainland Tanzania: simulation of the impact of strata-specific intervention combinations using modelling. Malar J 2022; 21:92. [PMID: 35300707 PMCID: PMC8929286 DOI: 10.1186/s12936-022-04099-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/23/2022] [Indexed: 11/21/2022] Open
Abstract
Background To accelerate progress against malaria in high burden countries, a strategic reorientation of resources at the sub-national level is needed. This paper describes how mathematical modelling was used in mainland Tanzania to support the strategic revision that followed the mid-term review of the 2015–2020 national malaria strategic plan (NMSP) and the epidemiological risk stratification at the council level in 2018. Methods Intervention mixes, selected by the National Malaria Control Programme, were simulated for each malaria risk strata per council. Intervention mixes included combinations of insecticide-treated bed nets (ITN), indoor residual spraying, larval source management, and intermittent preventive therapies for school children (IPTsc). Effective case management was either based on estimates from the malaria indicator survey in 2016 or set to a hypothetical target of 85%. A previously calibrated mathematical model in OpenMalaria was used to compare intervention impact predictions for prevalence and incidence between 2016 and 2020, or 2022. Results For each malaria risk stratum four to ten intervention mixes were explored. In the low-risk and urban strata, the scenario without a ITN mass campaign in 2019, predicted high increase in prevalence by 2020 and 2022, while in the very-low strata the target prevalence of less than 1% was maintained at low pre-intervention transmission intensity and high case management. In the moderate and high strata, IPTsc in addition to existing vector control was predicted to reduce the incidence by an additional 15% and prevalence by 22%. In the high-risk strata, all interventions together reached a maximum reduction of 76%, with around 70% of that reduction attributable to high case management and ITNs. Overall, the simulated revised NMSP was predicted to achieve a slightly lower prevalence in 2020 compared to the 2015–2020 NMSP (5.3% vs 6.3%). Conclusion Modelling supported the choice of intervention per malaria risk strata by providing impact comparisons of various alternative intervention mixes to address specific questions relevant to the country. The use of a council-calibrated model, that reproduces local malaria trends, represents a useful tool for compiling available evidence into a single analytical platform, that complement other evidence, to aid national programmes with decision-making processes. Supplementary Information The online version contains supplementary material available at 10.1186/s12936-022-04099-5.
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Affiliation(s)
- Manuela Runge
- Swiss Tropical and Public Health Institute, Basel, Switzerland. .,University of Basel, Basel, Switzerland.
| | - Sumaiyya G Thawer
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Fabrizio Molteni
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Frank Chacky
- National Malaria Control Programme, Dodoma, Tanzania.,Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
| | - Sigsbert Mkude
- National Malaria Control Programme, Dodoma, Tanzania.,Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
| | - Renata Mandike
- National Malaria Control Programme, Dodoma, Tanzania.,Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
| | - Robert W Snow
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.,Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Christian Lengeler
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Ally Mohamed
- National Malaria Control Programme, Dodoma, Tanzania.,Ministry of Health, Community Development, Gender, Elderly, and Children, Dodoma, Tanzania
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Basel, Switzerland. .,University of Basel, Basel, Switzerland. .,CHAI, Clinton Health Access Initiative, New York, USA.
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Hyde E, Bonds MH, Ihantamalala FA, Miller AC, Cordier LF, Razafinjato B, Andriambolamanana H, Randriamanambintsoa M, Barry M, Andrianirinarison JC, Andriamananjara MN, Garchitorena A. Estimating the local spatio-temporal distribution of malaria from routine health information systems in areas of low health care access and reporting. Int J Health Geogr 2021; 20:8. [PMID: 33579294 PMCID: PMC7879399 DOI: 10.1186/s12942-021-00262-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 01/19/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care. METHODS We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria. RESULTS Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations' financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years. CONCLUSIONS Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.
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Affiliation(s)
- Elizabeth Hyde
- Stanford University School of Medicine, Stanford, CA, USA
| | - Matthew H Bonds
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA
- NGO PIVOT, Ranomafana, Madagascar
| | - Felana A Ihantamalala
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA
- NGO PIVOT, Ranomafana, Madagascar
| | - Ann C Miller
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA
| | | | | | | | - Marius Randriamanambintsoa
- Direction de La Démographie et des Statistiques Sociales, Institut National de La Statistique, Antananarivo, Madagascar
| | - Michele Barry
- Stanford University School of Medicine, Stanford, CA, USA
- Center for Innovation in Global Health, Stanford University, Stanford, CA, USA
| | | | | | - Andres Garchitorena
- NGO PIVOT, Ranomafana, Madagascar.
- MIVEGEC, Univ. Montpellier, CNRS, IRD, Montpellier, France.
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Runge M, Molteni F, Mandike R, Snow RW, Lengeler C, Mohamed A, Pothin E. Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania. Malar J 2020; 19:101. [PMID: 32122342 PMCID: PMC7053121 DOI: 10.1186/s12936-020-03173-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 02/20/2020] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND More than ever, it is crucial to make the best use of existing country data, and analytical tools for developing malaria control strategies as the heterogeneity in malaria risk within countries is increasing, and the available malaria control tools are expanding while large funding gaps exist. Global and local policymakers, as well as funders, increasingly recognize the value of mathematical modelling as a strategic tool to support decision making. This case study article describes the long-term use of modelling in close collaboration with the National Malaria Control Programme (NMCP) in Tanzania, the challenges encountered and lessons learned. CASE DESCRIPTION In Tanzania, a recent rebound in prevalence led to the revision of the national malaria strategic plan with interventions targeted to the malaria risk at the sub-regional level. As part of the revision, a mathematical malaria modelling framework for setting specific predictions was developed and used between 2016 and 2019 to (1) reproduce setting specific historical malaria trends, and (2) to simulate in silico the impact of future interventions. Throughout the project, multiple stakeholder workshops were attended and the use of mathematical modelling interactively discussed. EVALUATION In Tanzania, the model application created an interdisciplinary and multisectoral dialogue platform between modellers, NMCP and partners and contributed to the revision of the national malaria strategic plan by simulating strategies suggested by the NMCP. The uptake of the modelling outputs and sustained interest by the NMCP were critically associated with following factors: (1) effective sensitization to the NMCP, (2) regular and intense communication, (3) invitation for the modellers to participate in the strategic plan process, and (4) model application tailored to the local context. CONCLUSION Empirical data analysis and its use for strategic thinking remain the cornerstone for evidence-based decision-making. Mathematical impact modelling can support the process both by unifying all stakeholders in one strategic process and by adding new key evidence required for optimized decision-making. However, without a long-standing partnership, it will be much more challenging to sensibilize programmes to the usefulness and sustained use of modelling and local resources within the programme or collaborating research institutions need to be mobilized.
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Affiliation(s)
- Manuela Runge
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Fabrizio Molteni
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- National Malaria Control Programme, Ministry of Health Community Development Gender Elderly and Children, Dodoma, Tanzania
| | - Renata Mandike
- National Malaria Control Programme, Ministry of Health Community Development Gender Elderly and Children, Dodoma, Tanzania
| | - Robert W Snow
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, OX3 7LJ, UK
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Christian Lengeler
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Ally Mohamed
- National Malaria Control Programme, Ministry of Health Community Development Gender Elderly and Children, Dodoma, Tanzania
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
- CHAI, Clinton Health Access Initative, Boston, USA.
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Runge M, Snow RW, Molteni F, Thawer S, Mohamed A, Mandike R, Giorgi E, Macharia PM, Smith TA, Lengeler C, Pothin E. Simulating the council-specific impact of anti-malaria interventions: A tool to support malaria strategic planning in Tanzania. PLoS One 2020; 15:e0228469. [PMID: 32074112 PMCID: PMC7029840 DOI: 10.1371/journal.pone.0228469] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 01/16/2020] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION The decision-making process for malaria control and elimination strategies has become more challenging. Interventions need to be targeted at council level to allow for changing malaria epidemiology and an increase in the number of possible interventions. Models of malaria dynamics can support this process by simulating potential impacts of multiple interventions in different settings and determining appropriate packages of interventions for meeting specific expected targets. METHODS The OpenMalaria model of malaria dynamics was calibrated for all 184 councils in mainland Tanzania using data from malaria indicator surveys, school parasitaemia surveys, entomological surveillance, and vector control deployment data. The simulations were run for different transmission intensities per region and five interventions, currently or potentially included in the National Malaria Strategic Plan, individually and in combination. The simulated prevalences were fitted to council specific prevalences derived from geostatistical models to obtain council specific predictions of the prevalence and number of cases between 2017 and 2020. The predictions were used to evaluate in silico the feasibility of the national target of reaching a prevalence of below 1% by 2020, and to suggest alternative intervention stratifications for the country. RESULTS The historical prevalence trend was fitted for each council with an agreement of 87% in 2016 (95%CI: 0.84-0.90) and an agreement of 90% for the historical trend (2003-2016) (95%CI: 0.87-0.93) The current national malaria strategy was expected to reduce the malaria prevalence between 2016 and 2020 on average by 23.8% (95% CI: 19.7%-27.9%) if current case management levels were maintained, and by 52.1% (95% CI: 48.8%-55.3%) if the case management were improved. Insecticide treated nets and case management were the most cost-effective interventions, expected to reduce the prevalence by 25.0% (95% CI: 19.7%-30.2) and to avert 37 million cases between 2017 and 2020. Mass drug administration was included in most councils in the stratification selected for meeting the national target at minimal costs, expected to reduce the prevalence by 77.5% (95%CI: 70.5%-84.5%) and to avert 102 million cases, with almost twice higher costs than those of the current national strategy. In summary, the model suggested that current interventions are not sufficient to reach the national aim of a prevalence of less than 1% by 2020 and a revised strategic plan needs to consider additional, more effective interventions, especially in high transmission areas and that the targets need to be revisited. CONCLUSION The methodology reported here is based on intensive interactions with the NMCP and provides a helpful tool for assessing the feasibility of country specific targets and for determining which intervention stratifications at sub-national level will have most impact. This country-led application could support strategic planning of malaria control in many other malaria endemic countries.
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Affiliation(s)
- Manuela Runge
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Robert W. Snow
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, England, United Kingodm
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Fabrizio Molteni
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- National Malaria Control Programme (NMCP), Dar es Salaam, Tanzania
| | - Sumaiyya Thawer
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- National Malaria Control Programme (NMCP), Dar es Salaam, Tanzania
| | - Ally Mohamed
- National Malaria Control Programme (NMCP), Dar es Salaam, Tanzania
| | - Renata Mandike
- National Malaria Control Programme (NMCP), Dar es Salaam, Tanzania
| | - Emanuele Giorgi
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, England, United Kingodm
| | - Peter M. Macharia
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Thomas A. Smith
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Christian Lengeler
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Emilie Pothin
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Clinton Health Access Initiative, Boston, Massachusetts, United States of America
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Miglianico M, Eldering M, Slater H, Ferguson N, Ambrose P, Lees RS, Koolen KMJ, Pruzinova K, Jancarova M, Volf P, Koenraadt CJM, Duerr HP, Trevitt G, Yang B, Chatterjee AK, Wisler J, Sturm A, Bousema T, Sauerwein RW, Schultz PG, Tremblay MS, Dechering KJ. Repurposing isoxazoline veterinary drugs for control of vector-borne human diseases. Proc Natl Acad Sci U S A 2018; 115:E6920-E6926. [PMID: 29967151 PMCID: PMC6055183 DOI: 10.1073/pnas.1801338115] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Isoxazolines are oral insecticidal drugs currently licensed for ectoparasite control in companion animals. Here we propose their use in humans for the reduction of vector-borne disease incidence. Fluralaner and afoxolaner rapidly killed Anopheles, Aedes, and Culex mosquitoes and Phlebotomus sand flies after feeding on a drug-supplemented blood meal, with IC50 values ranging from 33 to 575 nM, and were fully active against strains with preexisting resistance to common insecticides. Based on allometric scaling of preclinical pharmacokinetics data, we predict that a single human median dose of 260 mg (IQR, 177-407 mg) for afoxolaner, or 410 mg (IQR, 278-648 mg) for fluralaner, could provide an insecticidal effect lasting 50-90 days against mosquitoes and Phlebotomus sand flies. Computational modeling showed that seasonal mass drug administration of such a single dose to a fraction of a regional population would dramatically reduce clinical cases of Zika and malaria in endemic settings. Isoxazolines therefore represent a promising new component of drug-based vector control.
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Affiliation(s)
| | | | - Hannah Slater
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London SW7 2AZ, United Kingdom
| | - Neil Ferguson
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London SW7 2AZ, United Kingdom
| | - Pauline Ambrose
- The Liverpool Insect Testing Establishment, Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom
| | - Rosemary S Lees
- The Liverpool Insect Testing Establishment, Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom
| | | | - Katerina Pruzinova
- Department of Parasitology, Faculty of Science, Charles University, 116 36 Prague, Czech Republic
| | - Magdalena Jancarova
- Department of Parasitology, Faculty of Science, Charles University, 116 36 Prague, Czech Republic
| | - Petr Volf
- Department of Parasitology, Faculty of Science, Charles University, 116 36 Prague, Czech Republic
| | | | | | | | - Baiyuan Yang
- California Institute for Biomedical Research, La Jolla, CA 92037
| | | | - John Wisler
- California Institute for Biomedical Research, La Jolla, CA 92037
| | | | - Teun Bousema
- Department of Medical Microbiology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands
| | - Robert W Sauerwein
- TropIQ Health Sciences, 6534 Nijmegen, The Netherlands
- Department of Medical Microbiology, Radboud University Medical Center, 6525 Nijmegen, The Netherlands
| | - Peter G Schultz
- California Institute for Biomedical Research, La Jolla, CA 92037;
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Korenromp E, Hamilton M, Sanders R, Mahiané G, Briët OJT, Smith T, Winfrey W, Walker N, Stover J. Impact of malaria interventions on child mortality in endemic African settings: comparison and alignment between LiST and Spectrum-Malaria model. BMC Public Health 2017; 17:781. [PMID: 29143637 PMCID: PMC5688465 DOI: 10.1186/s12889-017-4739-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background In malaria-endemic countries, malaria prevention and treatment are critical for child health. In the context of intervention scale-up and rapid changes in endemicity, projections of intervention impact and optimized program scale-up strategies need to take into account the consequent dynamics of transmission and immunity. Methods The new Spectrum-Malaria program planning tool was used to project health impacts of Insecticide-Treated mosquito Nets (ITNs) and effective management of uncomplicated malaria cases (CMU), among other interventions, on malaria infection prevalence, case incidence and mortality in children 0–4 years, 5–14 years of age and adults. Spectrum-Malaria uses statistical models fitted to simulations of the dynamic effects of increasing intervention coverage on these burdens as a function of baseline malaria endemicity, seasonality in transmission and malaria intervention coverage levels (estimated for years 2000 to 2015 by the World Health Organization and Malaria Atlas Project). Spectrum-Malaria projections of proportional reductions in under-five malaria mortality were compared with those of the Lives Saved Tool (LiST) for the Democratic Republic of the Congo and Zambia, for given (standardized) scenarios of ITN and/or CMU scale-up over 2016–2030. Results Proportional mortality reductions over the first two years following scale-up of ITNs from near-zero baselines to moderately higher coverages align well between LiST and Spectrum-Malaria —as expected since both models were fitted to cluster-randomized ITN trials in moderate-to-high-endemic settings with 2-year durations. For further scale-up from moderately high ITN coverage to near-universal coverage (as currently relevant for strategic planning for many countries), Spectrum-Malaria predicts smaller additional ITN impacts than LiST, reflecting progressive saturation. For CMU, especially in the longer term (over 2022–2030) and for lower-endemic settings (like Zambia), Spectrum-Malaria projects larger proportional impacts, reflecting onward dynamic effects not fully captured by LiST. Conclusions Spectrum-Malaria complements LiST by extending the scope of malaria interventions, program packages and health outcomes that can be evaluated for policy making and strategic planning within and beyond the perspective of child survival. Electronic supplementary material The online version of this article (10.1186/s12889-017-4739-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Matthew Hamilton
- Avenir Health, 655 Winding Brook Drive, Glastonbury, CT-06033, USA
| | - Rachel Sanders
- Avenir Health, 655 Winding Brook Drive, Glastonbury, CT-06033, USA
| | - Guy Mahiané
- Avenir Health, 655 Winding Brook Drive, Glastonbury, CT-06033, USA
| | - Olivier J T Briët
- Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051, Basel, Switzerland.,Epidemiology and Public Health, University of Basel, Basel, Switzerland
| | - Thomas Smith
- Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051, Basel, Switzerland.,Epidemiology and Public Health, University of Basel, Basel, Switzerland
| | - William Winfrey
- Avenir Health, 655 Winding Brook Drive, Glastonbury, CT-06033, USA
| | - Neff Walker
- Department of International Health, Institute for International Programs, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD, 21205, USA
| | - John Stover
- Avenir Health, 655 Winding Brook Drive, Glastonbury, CT-06033, USA
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8
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Scott N, Hussain SA, Martin-Hughes R, Fowkes FJI, Kerr CC, Pearson R, Kedziora DJ, Killedar M, Stuart RM, Wilson DP. Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations. Malar J 2017; 16:368. [PMID: 28899373 PMCID: PMC5596957 DOI: 10.1186/s12936-017-2019-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2017] [Accepted: 09/06/2017] [Indexed: 11/30/2022] Open
Abstract
Background The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions. Methods A geospatial epidemic model was coupled with costing data and an optimization algorithm to estimate the optimal allocation of budgeted and projected funds across all malaria intervention approaches. Interventions included long-lasting insecticide-treated nets (LLINs), indoor residual spraying (IRS), intermittent presumptive treatment during pregnancy (IPTp), seasonal mass chemoprevention in children (SMC), larval source management (LSM), mass drug administration (MDA), and behavioural change communication (BCC). The model was applied to six geopolitical regions of Nigeria in isolation and also the nation as a whole to minimize incidence and malaria-attributable mortality. Results Allocative efficiency gains could avert approximately 84,000 deaths or 15.7 million cases of malaria in Nigeria over 5 years. With an additional US$300 million available, approximately 134,000 deaths or 37.3 million cases of malaria could be prevented over 5 years. Priority funding should go to LLINs, IPTp and BCC programmes, and SMC should be expanded in seasonal areas. To minimize mortality, treatment expansion is critical and prioritized over some LLIN funding, while to minimize incidence, LLIN funding remained a priority. For areas with lower rainfall, LSM is prioritized over IRS but MDA is not recommended unless all other programmes are established. Conclusions Substantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas. Electronic supplementary material The online version of this article (doi:10.1186/s12936-017-2019-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Nick Scott
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia. .,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.
| | - S Azfar Hussain
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Optima Consortium for Decision Science, Melbourne, Australia
| | | | - Freya J I Fowkes
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.,Department of Infectious Diseases, Monash University, Melbourne, Australia
| | - Cliff C Kerr
- Optima Consortium for Decision Science, Melbourne, Australia
| | - Ruth Pearson
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.,Optima Consortium for Decision Science, Melbourne, Australia
| | - David J Kedziora
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.,Optima Consortium for Decision Science, Melbourne, Australia
| | - Madhura Killedar
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.,Optima Consortium for Decision Science, Melbourne, Australia
| | - Robyn M Stuart
- Optima Consortium for Decision Science, Melbourne, Australia.,Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - David P Wilson
- Burnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Clayton, Australia.,Optima Consortium for Decision Science, Melbourne, Australia
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9
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Korenromp EL, Mahiané G, Rowley J, Nagelkerke N, Abu-Raddad L, Ndowa F, El-Kettani A, El-Rhilani H, Mayaud P, Chico RM, Pretorius C, Hecht K, Wi T. Estimating prevalence trends in adult gonorrhoea and syphilis in low- and middle-income countries with the Spectrum-STI model: results for Zimbabwe and Morocco from 1995 to 2016. Sex Transm Infect 2017; 93:599-606. [PMID: 28325771 PMCID: PMC5739862 DOI: 10.1136/sextrans-2016-052953] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 01/06/2017] [Accepted: 01/14/2017] [Indexed: 11/13/2022] Open
Abstract
Objective To develop a tool for estimating national trends in adult prevalence of sexually transmitted infections by low- and middle-income countries, using standardised, routinely collected programme indicator data. Methods The Spectrum-STI model fits time trends in the prevalence of active syphilis through logistic regression on prevalence data from antenatal clinic-based surveys, routine antenatal screening and general population surveys where available, weighting data by their national coverage and representativeness. Gonorrhoea prevalence was fitted as a moving average on population surveys (from the country, neighbouring countries and historic regional estimates), with trends informed additionally by urethral discharge case reports, where these were considered to have reasonably stable completeness. Prevalence data were adjusted for diagnostic test performance, high-risk populations not sampled, urban/rural and male/female prevalence ratios, using WHO's assumptions from latest global and regional-level estimations. Uncertainty intervals were obtained by bootstrap resampling. Results Estimated syphilis prevalence (in men and women) declined from 1.9% (95% CI 1.1% to 3.4%) in 2000 to 1.5% (1.3% to 1.8%) in 2016 in Zimbabwe, and from 1.5% (0.76% to 1.9%) to 0.55% (0.30% to 0.93%) in Morocco. At these time points, gonorrhoea estimates for women aged 15–49 years were 2.5% (95% CI 1.1% to 4.6%) and 3.8% (1.8% to 6.7%) in Zimbabwe; and 0.6% (0.3% to 1.1%) and 0.36% (0.1% to 1.0%) in Morocco, with male gonorrhoea prevalences 14% lower than female prevalence. Conclusions This epidemiological framework facilitates data review, validation and strategic analysis, prioritisation of data collection needs and surveillance strengthening by national experts. We estimated ongoing syphilis declines in both Zimbabwe and Morocco. For gonorrhoea, time trends were less certain, lacking recent population-based surveys.
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Affiliation(s)
| | - Guy Mahiané
- Avenir Health, Glastonbury, Connecticut, USA
| | | | | | - Laith Abu-Raddad
- Weill Cornell Medical College-Qatar, Cornell University, Doha, Qatar
| | - Francis Ndowa
- Skin & Genito-Urinary Medicine Clinic, Harare, Zimbabwe
| | - Amina El-Kettani
- Ministry of Health, Direction de l'Epidémiologie & Service de Maladies Sexuellement Transmissibles, Rabat, Morocco
| | | | | | | | | | | | - Teodora Wi
- Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland
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10
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Hamilton M, Mahiane G, Werst E, Sanders R, Briët O, Smith T, Cibulskis R, Cameron E, Bhatt S, Weiss DJ, Gething PW, Pretorius C, Korenromp EL. Spectrum-Malaria: a user-friendly projection tool for health impact assessment and strategic planning by malaria control programmes in sub-Saharan Africa. Malar J 2017; 16:68. [PMID: 28183343 PMCID: PMC5301449 DOI: 10.1186/s12936-017-1705-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 01/19/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Scale-up of malaria prevention and treatment needs to continue but national strategies and budget allocations are not always evidence-based. This article presents a new modelling tool projecting malaria infection, cases and deaths to support impact evaluation, target setting and strategic planning. METHODS Nested in the Spectrum suite of programme planning tools, the model includes historic estimates of case incidence and deaths in groups aged up to 4, 5-14, and 15+ years, and prevalence of Plasmodium falciparum infection (PfPR) among children 2-9 years, for 43 sub-Saharan African countries and their 602 provinces, from the WHO and malaria atlas project. Impacts over 2016-2030 are projected for insecticide-treated nets (ITNs), indoor residual spraying (IRS), seasonal malaria chemoprevention (SMC), and effective management of uncomplicated cases (CMU) and severe cases (CMS), using statistical functions fitted to proportional burden reductions simulated in the P. falciparum dynamic transmission model OpenMalaria. RESULTS In projections for Nigeria, ITNs, IRS, CMU, and CMS scale-up reduced health burdens in all age groups, with largest proportional and especially absolute reductions in children up to 4 years old. Impacts increased from 8 to 10 years following scale-up, reflecting dynamic effects. For scale-up of each intervention to 80% effective coverage, CMU had the largest impacts across all health outcomes, followed by ITNs and IRS; CMS and SMC conferred additional small but rapid mortality impacts. DISCUSSION Spectrum-Malaria's user-friendly interface and intuitive display of baseline data and scenario projections holds promise to facilitate capacity building and policy dialogue in malaria programme prioritization. The module's linking to the OneHealth Tool for costing will support use of the software for strategic budget allocation. In settings with moderately low coverage levels, such as Nigeria, improving case management and achieving universal coverage with ITNs could achieve considerable burden reductions. Projections remain to be refined and validated with local expert input data and actual policy scenarios.
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Affiliation(s)
- Matthew Hamilton
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
| | - Guy Mahiane
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
| | - Elric Werst
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
| | - Rachel Sanders
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
| | - Olivier Briët
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Thomas Smith
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Richard Cibulskis
- World Health Organization Global Malaria Programme, Geneva, Switzerland
| | - Ewan Cameron
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Samir Bhatt
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel J. Weiss
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Peter W. Gething
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Carel Pretorius
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
| | - Eline L. Korenromp
- Avenir Health, Geneva, 1 route de Morillons/150 Route de Ferney (WCC, office 164), PO box 2100, 1211 Geneva 2, Switzerland
- Avenir Health, Glastonbury, USA
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