Dataset Information

To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions.

ABSTRACT:

Background

Mass drug administration and mass-screen-and-treat interventions have been used to interrupt malaria transmission and reduce burden in sub-Saharan Africa. Determining which strategy will reduce costs is an important challenge for implementers; however, model-based simulations and field studies have yet to develop consensus guidelines. Moreover, there is often no way for decision-makers to directly interact with these data and/or models, incorporate local knowledge and expertise, and re-fit parameters to guide their specific goals.

Methods

We propose a general framework for comparing costs associated with mass drug administrations and mass screen and treat based on the possible outcomes of each intervention and the costs associated with each outcome. We then used publicly available data from six countries in western Africa to develop spatial-explicit probabilistic models to estimate intervention costs based on baseline malaria prevalence, diagnostic performance, and sociodemographic factors (age and urbanicity). In addition to comparing specific scenarios, we also develop interactive web applications which allow managers to select data sources and model parameters, and directly input their own cost values.

Results

The regional-level models revealed substantial spatial heterogeneity in malaria prevalence and diagnostic test sensitivity and specificity, indicating that a "one-size-fits-all" approach is unlikely to maximize resource allocation. For instance, urban communities in Burkina Faso typically had lower prevalence rates compared to rural communities (0.151 versus 0.383, respectively) as well as lower diagnostic sensitivity (0.699 versus 0.862, respectively); however, there was still substantial regional variation. Adjusting the cost associated with false negative diagnostic results to included additional costs, such as delayed treated and potential lost wages, undermined the overall costs associated with MSAT.

Conclusions

The observed spatial variability and dependence on specified cost values support not only the need for location-specific intervention approaches but also the need to move beyond standard modeling approaches and towards interactive tools which allow implementers to engage directly with data and models. We believe that the framework demonstrated in this article will help connect modeling efforts and stakeholders in order to promote data-driven decision-making for the effective management of malaria, as well as other diseases.

SUBMITTER: Millar J

PROVIDER: S-EPMC7304173 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions.

Millar Justin J Toh Kok Ben KB Valle Denis D

BMC medicine 20200619 1

<h4>Background</h4>Mass drug administration and mass-screen-and-treat interventions have been used to interrupt malaria transmission and reduce burden in sub-Saharan Africa. Determining which strategy will reduce costs is an important challenge for implementers; however, model-based simulations and field studies have yet to develop consensus guidelines. Moreover, there is often no way for decision-makers to directly interact with these data and/or models, incorporate local knowledge and expertis ...[more]

PMID: 32552743

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Project description:BackgroundThe control and elimination of malaria requires expanded coverage of and access to effective malaria control interventions such as insecticide-treated nets (ITNs), indoor residual spraying (IRS), intermittent preventive treatment (IPT), diagnostic testing and appropriate treatment. Decisions on how to scale up the coverage of these interventions need to be based on evidence of programme effectiveness, equity and cost-effectiveness.MethodsA systematic review of the published literature on the costs and cost-effectiveness of malaria interventions was undertaken. All costs and cost-effectiveness ratios were inflated to 2009 USD to allow comparison of the costs and benefits of several different interventions through various delivery channels, across different geographical regions and from varying costing perspectives.ResultsFifty-five studies of the costs and forty three studies of the cost-effectiveness of malaria interventions were identified, 78% of which were undertaken in sub-Saharan Africa, 18% in Asia and 4% in South America. The median financial cost of protecting one person for one year was $2.20 (range $0.88-$9.54) for ITNs, $6.70 (range $2.22-$12.85) for IRS, $0.60 (range $0.48-$1.08) for IPT in infants, $4.03 (range $1.25-$11.80) for IPT in children, and $2.06 (range $0.47-$3.36) for IPT in pregnant women. The median financial cost of diagnosing a case of malaria was $4.32 (range $0.34-$9.34). The median financial cost of treating an episode of uncomplicated malaria was $5.84 (range $2.36-$23.65) and the median financial cost of treating an episode of severe malaria was $30.26 (range $15.64-$137.87). Economies of scale were observed in the implementation of ITNs, IRS and IPT, with lower unit costs reported in studies with larger numbers of beneficiaries. From a provider perspective, the median incremental cost effectiveness ratio per disability adjusted life year averted was $27 (range $8.15-$110) for ITNs, $143 (range $135-$150) for IRS, and $24 (range $1.08-$44.24) for IPT.ConclusionsA transparent evidence base on the costs and cost-effectiveness of malaria control interventions is provided to inform rational resource allocation by donors and domestic health budgets and the selection of optimal packages of interventions by malaria control programmes.

Project description:BackgroundMedication adherence is an important but highly complex set of behaviors, which for life-threatening and infectious diseases such as HIV carry critical consequences for individual and public health. There is growing evidence that mobile phone text messaging interventions (mHealth) connecting providers with patients positively impact medication adherence, particularly two-way engagement platforms that require bidirectional communication versus one-way in which responses are not mandatory. However, mechanisms of action have not been well defined. The Behavior Change Wheel is a comprehensive framework for behavior change that includes an all-encompassing model of behavior known as Capability Opportunity Motivation-Behavior and is complemented by a taxonomy of behavior change techniques. Evaluating mHealth interventions for medication adherence using these tools could provide useful insights that may contribute to optimizing their integration into the healthcare system and successful scaling-up.ObjectiveThis study aimed to help address the current knowledge gap regarding how two-way mHealth interventions for medication adherence may work by applying the Behavior Change Wheel to characterize WelTel: an interactive digital health outreach platform with robust evidence for improving adherence to antiretroviral therapy.MethodsTo characterize how WelTel may promote medication adherence, we applied the Behavior Change Wheel to systematically (1) generate a behavioral diagnosis through mapping known antiretroviral therapy adherence barriers onto the Capability Opportunity Motivation-Behavior model of behavior, (2) specify the behavior change techniques that WelTel delivers, (3) link identified behavior change techniques to corresponding intervention functions of the Behavior Change Wheel, and (4) connect these behavior change techniques and intervention functions to respective Capability Opportunity Motivation-Behavior influences on behavior to determine potential mechanisms of action.ResultsOur evaluation of WelTel using the Behavior Change Wheel suggests that most of its impact is delivered primarily through its personalized communication component, in which 8 different behavior change techniques were identified and linked with 5 intervention functions (environmental restructuring, enablement, education, persuasion, and training). Its mechanisms of action in promoting antiretroviral therapy adherence may involve addressing all Capability Opportunity Motivation-Behavior influences on behavior (physical and psychological capability, physical and social opportunity, reflective and automatic motivation).ConclusionsSystematically unpacking the potential active ingredients of effective interventions facilitates the creation and implementation of more parsimonious, tailored, and targeted approaches. Evaluating WelTel using the Behavior Change Wheel has provided valuable insights into how and why such interactive two-way mHealth interventions may produce greater impact than one-way in addressing both nonintentional and intentional forms of nonadherence. The application of the Behavior Change Wheel for evidence synthesis across mHealth interventions targeting various conditions would contribute to strengthening the knowledge base regarding how they may work to impact medication adherence behavior.

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Project description:Background?Community health workers (CHWs) were trained in Burkina Faso, Nigeria, and Uganda to diagnose febrile children using malaria rapid diagnostic tests, and treat positive malaria cases with artemisinin-based combination therapy (ACT) and those who could not take oral medicines with rectal artesunate. We quantified the impact of this intervention on private household costs for childhood febrile illness.Methods?Households with recent febrile illness in a young child in previous 2 weeks were selected randomly before and during the intervention and data obtained on household costs for the illness episode. Household costs included consultation fees, registration costs, user fees, diagnosis, bed, drugs, food, and transport costs. Private household costs per episode before and during the intervention were compared. The intervention's impact on household costs per episode was calculated and projected to districtwide impacts on household costs.Results?Use of CHWs increased from 35% of illness episodes before the intervention to 50% during the intervention (P < .0001), and total household costs per episode decreased significantly in each country: from US Dollars (USD) $4.36 to USD $1.54 in Burkina Faso, from USD $3.90 to USD $2.04 in Nigeria, and from USD $4.46 to USD $1.42 in Uganda (all P < .0001). There was no difference in the time used by the child's caregiver to care for a sick child (59% before intervention vs 51% during intervention spent ?2 days). Using the most recent population figures for each study district, we estimate that the intervention could save households a total of USD $29 965, USD $254 268, and USD $303 467, respectively, in the study districts in Burkina Faso, Nigeria, and Uganda.Conclusions?Improving access to malaria diagnostics and treatments in malaria-endemic areas substantially reduces private household costs. The key challenge is to develop and strengthen community human resources to deliver the intervention, and ensure adequate supplies of commodities and supervision. We demonstrate feasibility and benefit to populations living in difficult circumstances.Clinical trials registration?ISRCTN13858170.

Dataset Information

To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions.

Background

Methods

Results

Conclusions

Publications

To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions.

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