Abstract
Introduction
Seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine and amodiaquine (SPAQ) has been delivered in sub-Saharan Africa since 2014, reaching over 40 million children in 2022. New questions are emerging related to SMC’s sustainability, integration with other interventions and introduction to new regions. Meanwhile, new WHO malaria guidelines have substantially increased flexibility for tailoring malaria strategies to local contexts. The SMC Alliance, bringing together researchers and implementers, commissioned a consultation to identify medium-term SMC research priorities.
Methods
The consultation was conducted online from September 2022 to September 2023 using the eDelphi methodology. An initial list of 46 research priorities was compiled during a workshop with SMC implementers. The wider expert consultation comprised three waves of online surveys available in English, French and Portuguese. Respondents rated research priorities on their importance, feasibility and degree to which they had already been addressed; responses determined elimination or retention of research priorities after each survey wave. Respondents suggested their own research priorities for rating. We also collected anonymised data on respondents’ characteristics. A final ranking exercise was conducted to reach consensus on a top 10 list of research priorities.
Results
A total of 67 unique respondents residing in 20 countries provided 96 survey responses. The surveys achieved balanced representation of respondents by gender, country of residence and professional background. Of the 25 research priorities retained for ranking, the highest-ranked included ‘evaluate duration of prophylactic protection offered by SPAQ and other SMC medicines’ and ‘evaluate the effect of integrating SMC with other malaria prevention interventions on development of antimalarial resistance’.
Conclusions
Research priorities related to sustainability, antimalarial resistance, integration with other interventions and improving quality of SMC delivery featured prominently among the highest-ranked research priorities. It is hoped the results of this consultation can encourage research uptake, guide new research and inform programme adaptation.
Keywords: Malaria, Health services research, Chemoprophylaxis
WHAT IS ALREADY KNOWN ON THIS TOPIC
While new WHO guidelines on seasonal malaria chemoprevention (SMC) increase implementers’ flexibility in campaign targeting and implementation in various dimensions, to date no systematic prioritisation of SMC research priorities exists.
WHAT THIS STUDY ADDS
This work systematically identified medium-term research priorities for SMC, operationalised as actionable research aims.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
This exercise can catalyse new research and encourage uptake of existing evidence to improving quality of delivery, effectiveness and sustainability of SMC.
Introduction
Seasonal malaria chemoprevention
In 2022 the WHO African Region had an estimated 580 000 malaria deaths, of these 78.1% occurred in children aged under 5 years.1 In large parts of the Region, the majority of malaria cases and deaths occur during a 3-month to 5-month window corresponding to the rainy season.2 Seasonal malaria chemoprevention (SMC) is an intervention recommended by the WHO to provide protection against Plasmodium falciparum malaria to age groups at high risk of severe malaria during the period of highest risk in areas where transmission is highly seasonal. The most recent guidelines identify priority target areas for SMC as those where at least 60% of annual cases occur within a consecutive 4-month period, and with a clinical attack rate of ≥0.1 per high transmission season in the target age group.3
Although alternative medicines such as dihydroartemisinin-piperaquine have been trialled,4 SMC has most commonly involved intermittent administration of courses of sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ) 28 days apart, corresponding to the expected period of protection, delivered in annual rounds of three to five cycles by community distributors through door-to-door campaigns during the high-transmission season.3 5 A dose of SP and the first dose of AQ (‘Day 1 SPAQ’) are administered by or under the supervision of community distributors to ensure that tablets are correctly dispersed in water and that the child fully ingests the medicine without spitting or vomiting (directly observed treatment). Two further AQ doses are administered at home once daily by caregivers (‘Day 2 AQ’ and ‘Day 3 AQ’). SMC with SPAQ has been shown to be safe, feasible, effective and cost-effective for the prevention of malaria cases in targeted populations.6 In 2022, 49 million children in Africa received SMC per cycle in the 17 countries where the intervention was delivered.1
Recent developments in SMC and rationale for the project
SMC has been scaled up since 2014 through the Achieving Catalytic Expansion of SMC in the Sahel (ACCESS-SMC) project7,9; while the initial Unitaid-funded project covered seven countries and involved a consortium including Malaria Consortium, Catholic Relief Services and Medicines for Malaria Venture among others, subsequent expansion has been underpinned by successful collaboration between national malaria control programmes, implementation partners and a range of international donors including the Global Fund, the President’s Malaria Initiative and the Bill and Melinda Gates Foundation.10 However, now that scale-up has been achieved, the operational focus of SMC has changed. Questions for the future of SMC include the potential for emergence of SPAQ resistance in circulating parasites, and whether SMC can be scaled up to new geographies. In addition, protocols for SMC delivery may be adapted considering new WHO guidelines: adaptations may include changes in age ranges, interval between cycles, numbers of cycles, distribution strategies, observation of SMC administration by community distributors, medicines employed and areas eligible for SMC delivery.3 The new guidelines expand both the scope of addressable SMC implementation research topics and potential adaptations to SMC delivery. Furthermore, according to the most recent WHO guidelines for malaria,11 the relevant Guideline Development Group (GDG) on malaria chemotherapy highlighted the need for further research on SMC and identified six major research gaps. These research gaps include the operational effectiveness of SMC; the value of administering SMC to children ≥10 years old; the effectiveness of SMC in areas with seasonal but >6 months of high malaria transmission; the effectiveness of SMC in areas with antimalarial drug resistance; the pharmacokinetics of drugs used for chemoprevention and concentrations required to prevent parasite growth (as opposed to therapeutic concentrations), and; the efficacy and effectiveness of delivering SMC with other drug combinations and intervals between cycles.
SMC research priorities setting exercise
The SMC Alliance (smc-alliance.org), a workstream under the RBM Partnership to End Malaria Country/Regional Support Partner Committee,10 is a group of stakeholders involved in SMC delivery, bringing together representatives of multilateral organisations, funders, implementing partners from government agencies and non-governmental organisations, and researchers across various countries. Within this alliance, a research subgroup has been created to share relevant research results and good practice, as well as explore future research priorities for SMC. In late 2022, the subgroup commissioned a collaborative research priorities setting exercise.
Study aim
The study, which represents a direct response to calls from SMC members to address pressing research gaps,10 aimed to reach consensus on a ranked list of medium-term SMC research priorities (over the next 5–10 years) while achieving inclusive representation of respondents by their individual demographic characteristics, including preferred language, gender, professional background (represented by organisation type of current employer) and geographies of residence. We also investigated whether responses differed by demographic characteristics. Research priorities were operationalised as actionable research aims.
Methods
The eDelphi methodology
The consultation was undertaken using the eDelphi methodology,12 originally developed by the RAND Corporation and commonly employed for scoping and prioritisation exercises. It is defined as ‘a process used to arrive at a group opinion or decision by surveying a panel of experts…’.13 Using this methodology, ‘experts respond to several rounds of questionnaires, and the responses are aggregated and shared with the group after each round…’.14
We followed a three-stage eDelphi approach adapted from Okoli and Pawlowski.15 This method was selected given its pragmatic nature, geographical distribution of relevant respondents and reduced time commitment from expert participants. This methodology has been widely used for health research and policy priority-setting, with the online adaptation notable for its participant retention and satisfaction.16 While these exercises may involve participant discussion sessions after surveys, anonymity can minimise pressure to conform to a group position.12 The design, implementation and reporting of this study was informed by the CREDES (Conducting and REporting DElphi Studies) guidelines (see online supplemental box 1).17
Study design
First, to identify initial research priorities to be rated by eDelphi participants in subsequent surveys, a structured 1-hour workshop was held at Malaria Consortium, a UK-based not-for-profit organisation (https://www.malariaconsortium.org), among all five available country technical coordinators from the widest-possible range of Africa-based offices supporting SMC implementation (including Burkina Faso, Chad, Togo, Mozambique and Uganda) to define initial research priorities.
These research priorities were then rated by respondents through successive online surveys, consisting of two Waves (1 and 2) of research priority rating and elimination, and a third (Wave 3), consisting of a final ranking exercise. All surveys were designed to take under 20 min. After each survey, online results summary presentations were given at SMC Alliance Research Subgroup meetings.
Sampling and respondents
We electronically recruited experts on SMC, who were generally defined as clinicians, researchers, technical partners and implementers, government employees and academics who have actively worked in SMC or a closely-related area within the last 5 years. We aimed to recruit around half of respondents from malaria-endemic African countries while maintaining gender balance and representation of employees of different organisation types. Each survey targeted a minimum of 50 respondents; these were recruited via snowball sampling from contacts of the research team, the SMC Alliance mailing list and SMC Alliance members’ contacts.
Survey methods
Online surveys took place between September 2022 and September 2023. All surveys were available in English and French, and Waves 2 and 3 were also available in Portuguese. Participants accessed the surveys in SurveyCTO through an anonymous link accessible via both computer and mobile devices.
The Wave 1 and Wave 2 surveys focused on the rating of research priorities following questions on respondent characteristics including gender (man/woman), age group (10-year age brackets), organisation type of current employer (non-governmental organisation/university or research institution/government or medical facility/private sector), self-reported country of origin and current country of residence.
Research priorities were rated on 5-point Likert scales (scored from 1 to 5, see online supplemental box 2) based on the dimensions of importance, feasibility and the degree to which they had already been addressed. All rating questions allowed respondents to indicate that they felt unable to rate this research priority. Finally, Wave 1 included sections allowing respondents to propose new research priorities not included in the survey, to be rated by their peers in Wave 2. After Wave 1, new research priorities were collated and merged into new research priority items if they overlapped for inclusion in the Wave 2 questionnaire.
Based on methods employed by the research team in a previous study,18 rated research priorities with ≥70% agreement on both their importance and feasibility (ie, scores of ≥4) in Wave 1 were retained for the Wave 2 survey, along with the new research priorities proposed by respondents.
Wave 3 consisted of a ranking exercise of the remaining research priorities after elimination of lower-rated priorities in Wave 2 using the same method as the Wave 1 survey. Before accessing the Wave 3 survey, respondents were encouraged to view an attachment (available in English, French and Portuguese) summarising the results of the Wave 2 survey and highlighting all remaining research priorities in Wave 3 ranked in order of average importance score.
Respondents ranked the remaining research priorities with ≥70% agreement on both importance and feasibility. Questions were implemented using the ranking-choices SurveyCTO field plugin.19 Remaining priorities were shown in a random order and participants dragged tiles representing each remaining research priority item into their desired ranking order from 1 to 25. Participants could then view their ranked list and readjust their ranking before submission.
Statistical analysis
We first described the characteristics of the respondents in each survey wave, and their retention between waves. We then described the scores of importance, feasibility and degree to which they had already been addressed for each research priority rated in Waves 1 and 2. We constructed the final rankings using two approaches: a simple scaled rank score (assigning 25 points for the 1st rank, down to 1 point for the 25th rank) and a reciprocal rank score (assigning 1 point for the 1st rank and 1/25 points for the 25th rank, giving greater weight to top rankings) as a sensitivity analysis. The simple scaled rank score provides a straightforward interpretation by treating intervals between ranks as equal, while the reciprocal rank method emphasises the relative importance of top-ranked priorities, reflecting their disproportionately higher importance in decision-making contexts.18 We then conducted statistical analyses stratifying rankings by respondents’ country of current residence (Africa vs other geographies), and by employment in academia versus other organisation types.18 Kendall’s τ rank correlation coefficient was used to measure the ordinal association between overall ranks by these subgroups based on the simple scaled ranking. Finally, we tested whether individual research priorities were given different ranks according to respondent characteristics (based in Africa vs other geographies; employment in academia vs other organisation types) using Mann-Whitney U tests. All statistical analyses were performed in Stata V.18.20
Ethics
Participants were provided with study information and requested to electronically confirm consent at the start of each web survey by responding ‘yes’ to six statements. Country technical coordinators participating in the initial research priorities workshop were read the same information before the start of the workshop and gave their verbal consent to participate. Participation in the initial workshop or online surveys was not remunerated. Online supplemental box 3 shows the online consent form delivered during the surveys.
Results
Respondent characteristics
Table 1 shows the characteristics of the respondents in each survey wave. A total of 96 responses, including 30 in Wave 1, 25 in Wave 2 and 41 in Wave 3, were received from 67 unique respondents residing in 20 different countries. Eight respondents from Wave 1 participated in the Wave 2 survey, representing a retention rate of 27% with 17 new respondents not present in Wave 1. In Wave 3, 21 respondents from either Wave 1 or Wave 2 participated, representing a retention rate of 51% with 20 new respondents not present in either of the previous waves. Our respondent sample achieved gender balance and represented a range of organisation types and countries across all survey waves. Figure 1 summarises respondents’ countries of residence and origin across the survey waves.
Table 1. Characteristics of respondents by survey wave.
| Respondent characteristics | Wave 1 | Wave 2 | Wave 3 | ||||
|---|---|---|---|---|---|---|---|
| Variable | Category | n | % | n | % | n | % |
| Gender | Man | 19 | 63.3 | 15 | 60.0 | 26 | 63.4 |
| Woman | 11 | 36.7 | 10 | 40.0 | 15 | 36.6 | |
| Survey language | English | 21 | 70.0 | 16 | 64.0 | 21 | 51.2 |
| French | 9 | 30.0 | 6 | 24.0 | 18 | 43.9 | |
| Portuguese | N/A | N/A | 3 | 12.0 | 2 | 4.9 | |
| Organisation type | Non-governmental organisation | 13 | 43.3 | 9 | 36.0 | 18 | 43.9 |
| University/research institution | 13 | 43.3 | 8 | 32.0 | 7 | 17.1 | |
| Government/clinic/hospital | 2 | 6.7 | 7 | 35.0 | 11 | 26.8 | |
| Private sector/other | 2 | 6.7 | 1 | 5.0 | 5 | 12.2 | |
| Country of residence | Africa | 17 | 56.7 | 11 | 44.0 | 27 | 65.9 |
| Other geographies | 13 | 43.3 | 14 | 56.0 | 14 | 34.1 | |
| Total | 30 | 100 | 25 | 100 | 41 | 100 | |
N/A, not assessed.
Figure 1. World map summarising countries of residence of eDelphi respondents. Dark blue: respondents in both Wave 1 and/or Wave 2, and Wave 3. Mid blue: respondents in Wave 3 but not Wave 1 or 2. Light blue: respondents in Wave 1 and Wave 2, but not Wave 3. Grey: any survey wave included respondents born in these countries, but currently residing elsewhere. Light green: respondents in initial priority-setting workshop but not eDelphi surveys.
Survey waves and priorities identified
There were a total of 46 research priorities at the start of the study following the initial priority-setting workshop (online supplemental table S1); 22 were retained after rating by respondents in Wave 1. There were a total of 59 research priorities in Wave 2 (online supplemental table S2) after the addition of 37 new research priorities suggested by respondents in Wave 1. Following analysis of Wave 2 survey responses, 25 research priorities were retained and included in the Wave 3 final ranking exercise. We noted, however, that for 5 of the 25 remaining research priorities, a high proportion of respondents (>33%) agreed or strongly agreed that they had already been addressed. These included: ‘Evaluate duration of prophylactic protection offered by SP+AQ and other SMC medicines’; ‘Evaluate the feasibility and impact of extension of SMC to children aged over five years and identify optimal age ranges for SMC eligibility in different settings’; ‘Design and evaluate new methods for improving delivery of amodiaquine on Day 2 and Day 3, and impacts on caregiver adherence to the full course of SMC medicines’; ‘Evaluate cost-effectiveness of SMC (in terms of cost per reduction in DALYs lost due to malaria)’, and; ‘Evaluate different strategies for achieving high adherence by caregivers to day 2 and day 3 AQ administration in different transmission contexts’.
Table 2 shows the rankings of the remaining 25 research priorities obtained from the Wave 3 exercise, calculated based on simple scaled scores and reciprocal rank scores; of these, 13 were suggested by respondents in Wave 1 and retained for the final ranking. While the research priority ‘Evaluate duration of prophylactic protection offered by SP+AQ and other SMC medicines’ was first-ranked based on the simple scaled score method, it was ranked eighth using reciprocal rank scores; this finding suggests that this research priority, although having the highest mean rank, received relatively fewer first or second ranks from respondents. Meanwhile, ‘Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on development of antimalarial resistance’ was highest-ranked based on the reciprocal rank score method and second using simple scaled scores.
Table 2. Summary of overall rankings of SMC research priorities by ranking method based on the Wave 3 ranking exercise.
| Simple scaled rank | Reciprocal rank score | Research priorities |
|---|---|---|
| 1 | 8 | Evaluate duration of prophylactic protection offered by SP+AQ and other SMC medicines. |
| 2 | 1 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on development of antimalarial resistance.* |
| 3 | 3 | Investigate the potential for ‘rebound effects’ in malaria incidence in older children as a result of SMC campaigns. |
| 4 | 6 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on SMC impact on malaria-related outcomes.* |
| 5 | 2 | Evaluate and compare impact of new/different drug regimens (eg, dihydroartemisinin-piperaquine) on malaria outcomes. |
| 6 | 4 | Design and evaluate new methods for improving delivery of AQ on Day 2 and Day 3, and impacts on caregiver adherence to the full course of SMC medicines.* |
| 7 | 14 | Evaluate the degree to which eligible children in different transmission settings (ie, according to seasonality and attack rate) benefit from SMC programmes; evaluate differential impact in different settings. |
| 8 | 5 | Evaluate the impact of SMC on asymptomatic malaria infection among eligible children.* |
| 9 | 7 | Evaluate different strategies for achieving high adherence by caregivers to day 2 and day 3 AQ administration in different transmission contexts. |
| 10 | 18 | Evaluate the feasibility and impact of extension of SMC to children aged over 5 years and identify optimal age ranges for SMC eligibility in different settings. |
| 11 | 13 | Investigate the relationship between molecular markers of antimalarial drug resistance and recurrent malaria in SMC.* |
| 12 | 9 | Evaluate the potential cost-benefit of digitising data collection at the household level and the investment case for digitised SMC campaigns.* |
| 13 | 12 | Design and evaluate models for using the SMC platform for delivering other health interventions, and evaluate the impacts of combining interventions for quality of SMC delivery.* |
| 14 | 16 | Assess the long-term effectiveness and sustainability of different social and behaviour change approaches on SMC and the duration of their impact on intervention uptake. |
| 15 | 25 | Investigate optimal timing of switching medicines used for chemoprevention to reduce or prevent emergence of antimalarial resistance. |
| 16 | 10 | Develop and evaluate new rapid assessment methodologies to support the introduction of SMC to new countries/settings. |
| 17 | 11 | Test and evaluate different delivery mechanisms to reach and sustain high coverage of SMC among hard-to-reach and highest risk populations (could be nomads, socioeconomically disadvantaged populations, regional ethnic minorities, religious minorities, etc). |
| 18 | 19 | Evaluate cost-effectiveness of SMC (in terms of cost per reduction in DALYs lost due to malaria). |
| 19 | 15 | Develop and evaluate standardised qualitative research tools to understand challenges identified in LQAS surveys about why children were not treated in each cycle.* |
| 20 | 20 | Investigate how prevalence of SP resistance alleles in circulating P. falciparum parasites (and their associations including quintuple and sextuple dhfr-dhps mutants) is associated with less effective parasite clearance of asymptomatic infections, protective efficacy and effectiveness of SMC.* |
| 21 | 17 | Investigate the potential implications of expansion of the eligible age range for SMC in terms of selection of resistance alleles among circulating P. falciparum parasites.* |
| 22 | 23 | Test and evaluate use of digital tools by SMC community distributors to improve quality of SMC delivery.* |
| 23 | 24 | Develop and evaluate new techniques for malaria risk mapping for SMC planning purposes. |
| 24 | 22 | Analyse determinants of spatiotemporal inequalities in SMC coverage and other outcomes.* |
| 25 | 21 | Develop and evaluate models to improve delivery of SMC to populations living in international border areas.* |
Research priority proposed by respondent(s) in the Wave 1 survey and included in the final ranking exercise.
AQ, amodiaquine; DALYs, disability-adjusted life years; LQAS, lot quality assurance sampling; SMC, seasonal malaria chemoprevention; SP, sulfadoxine-pyrimethamine.
Differences in rankings by respondent groups
Table 3 shows the top 10 rankings in the Wave 3 survey using simple scaled scores stratified by country of current residence (Africa vs other geographies). While ‘Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on development of antimalarial resistance’ was highest-ranked among Africa-based respondents, this research priority was ranked sixth among other respondents. Meanwhile, ‘Evaluate the degree to which eligible children in different transmission settings (ie, according to seasonality and attack rate) benefit from SMC programmes; evaluate differential impact in different settings’ was highest-ranked among respondents based in other geographies. Online supplemental table S3 shows the top 10 ranking stratified by organisation type of current employer.
Table 3. Top 10 rankings in the Wave 3 survey stratified by country of current residence (Africa vs other geographies, simple scaled rank score method).
| Africa-based | Other geographies | ||
|---|---|---|---|
| 1 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on development of antimalarial resistance. | 1 | Evaluate the degree to which eligible children in different transmission settings (ie, according to seasonality and attack rate) benefit from SMC programmes; evaluate differential impact in different settings. |
| 2 | Evaluate the duration of prophylactic protection offered by SP+AQ and other SMC medicines. | 2 | Evaluate and compare impact of new/different drug regimens (eg, dihydroartemisinin-piperaquine) on malaria outcomes. |
| 3 | Design and evaluate new methods for improving delivery of AQ on Day 2 and Day 3, and impacts on caregiver adherence to the full course of SMC medicines. | 3 | Evaluate the duration of prophylactic protection offered by SP+AQ and other SMC medicines. |
| 4 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on SMC impact on malaria-related outcomes. | 4 | Investigate the potential for ‘rebound effects’ in malaria incidence in older children as a result of SMC campaigns. |
| 5 | Investigate the potential for ‘rebound effects’ in malaria incidence in older children as a result of SMC campaigns. | 5 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on SMC impact on malaria-related outcomes. |
| 6 | Evaluate different strategies for achieving high adherence by caregivers to day 2 and day 3 AQ administration in different transmission contexts. | 6 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on the development of antimalarial resistance. |
| 7 | Investigate the relationship between molecular markers of antimalarial drug resistance and recurrent malaria in SMC. | 7 | Evaluate cost-effectiveness of SMC (in terms of cost per reduction in DALYs lost due to malaria). |
| 8 | Evaluate the potential cost-benefit of digitising data collection at the household level and the investment case for digitised SMC campaigns. | 8 | Develop and evaluate new rapid assessment methodologies to support the introduction of SMC to new countries/settings. |
| 9 | Evaluate the feasibility and impact of extension of SMC to children aged over 5 years and identify optimal age ranges for SMC eligibility in different settings. | 9 | Evaluate the impact of SMC on asymptomatic malaria infection among eligible children. |
| 10 | Evaluate the impact of SMC on asymptomatic malaria infection among eligible children. | 10 | Test and evaluate different delivery mechanisms to reach and sustain high coverage of SMC among hard-to-reach and highest risk populations (could be nomads, socioeconomically disadvantaged populations, regional ethnic minorities, religious minorities, etc). |
AQ, amodiaquine; DALYs, disability-adjusted life years; LQAS, lot quality assurance sampling; SMC, seasonal malaria chemoprevention; SP, sulfadoxine-pyrimethamine.
Kendall’s τ rank correlation coefficients for the ordinal association between overall ranks derived from the Wave 3 survey (using the simple scaled method) and participant characteristics were 0.260 for current country of residence and 0.220 for organisation type of current employer; p values were 0.072 and 0.129, respectively. These findings indicate weak correlation between rankings from respondents residing in Africa and other geographies, and between those from respondents working in academia or research institutes and those employed in other organisation types; differences in rankings by these two participant characteristics were not statistically significant at the 95% confidence level, suggesting that it could not be concluded that rankings between groups were independent of one another.
Table 4 shows results of Mann-Whitney U tests for differences in rankings by respondent characteristics, including Mann-Whitney U statistics and p values. While we found that respondents residing in Africa gave significantly lower ranks to the research priority ‘Investigate the potential implications of expansion of the eligible age range for SMC in terms of selection of resistance alleles among circulating P. falciparum parasites’ than those residing in other geographies, the research priorities ‘Evaluate duration of prophylactic protection offered by SP+AQ and other SMC medicines’ and ‘Design and evaluate models for using the SMC platform for delivering other health interventions, and evaluate the impacts of combining interventions for quality of SMC delivery’ were given significantly lower rank scores by respondents currently working in academia or research institutions than those employed in other organisation types (p<0.05).
Table 4. Results of Mann-Whitney U tests for differences in rankings by respondent characteristics.
| Research priorities by scaled mean rank score | Africa versus other geographies | Academic versus other | |||
|---|---|---|---|---|---|
| 1 | Evaluate duration of prophylactic protection offered by SP+AQ and other SMC medicines. | −0.234 | 0.8223 | 2.572 | 0.008* |
| 2 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on development of antimalarial resistance. | −1.047 | 0.3025 | −0.364 | 0.7278 |
| 3 | Investigate the potential for ‘rebound effects’ in malaria incidence in older children as a result of SMC campaigns. | 0.868 | 0.3937 | 0.087 | 0.9389 |
| 4 | Evaluate the effect of integrating SMC with other malaria prevention interventions (eg, vaccines) on SMC impact on malaria-related outcomes. | 1.46 | 0.1477 | 1.267 | 0.2131 |
| 5 | Evaluate and compare impact of new/different drug regimens (eg, dihydroartemisinin-piperaquine) on malaria outcomes. | 1.611 | 0.1093 | −1.701 | 0.0911 |
| 6 | Design and evaluate new methods for improving delivery of AQ on Day 2 and Day 3, and impacts on caregiver adherence to the full course of SMC medicines. | −1.723 | 0.0863† | 1.285 | 0.2067 |
| 7 | Evaluate the degree to which eligible children in different transmission settings (ie,according to seasonality and attack rate) benefit from SMC programmes; evaluate differential impact in different settings. | −0.771 | 0.4495 | −0.85 | 0.4092 |
| 8 | Evaluate the impact of SMC on asymptomatic malaria infection among eligible children. | 0.633 | 0.5355 | 0.833 | 0.4192 |
| 9 | Evaluate different strategies for achieving high adherence by caregivers to day 2 and day 3 AQ administration in different transmission contexts. | −0.634 | 0.5354 | 1.771 | 0.0779* |
| 10 | Evaluate the feasibility and impact of extension of SMC to children aged over 5 years and identify optimal age ranges for SMC eligibility in different settings. | 1.418 | 0.1599 | −0.087 | 0.9395 |
| 11 | Investigate the relationship between molecular markers of antimalarial drug resistance and recurrent malaria in SMC. | −1.405 | 0.164 | 0.069 | 0.9528 |
| 12 | Evaluate the potential cost-benefit of digitising data collection at the household level and the investment case for digitised SMC campaigns. | 0.578 | 0.5722 | −1.284 | 0.2071 |
| 13 | Design and evaluate models for using the SMC platform for delivering other health interventions, and evaluate the impacts of combining interventions for quality of SMC delivery. | −1.075 | 0.2895 | −1.979 | 0.0474* |
| 14 | Assess the long-term effectiveness and sustainability of different social and behaviour change approaches on SMC and the duration of their impact on intervention uptake. | 0.289 | 0.7805 | −0.364 | 0.7283 |
| 15 | Investigate optimal timing of switching medicines used for chemoprevention to reduce or prevent emergence of antimalarial resistance. | −0.537 | 0.6002 | −0.017 | 0.9934 |
| 16 | Develop and evaluate new rapid assessment methodologies to support the introduction of SMC to new countries/settings. | −0.041 | 0.9729 | −0.833 | 0.4181 |
| 17 | Test and evaluate different delivery mechanisms to reach and sustain high coverage of SMC among hard-to-reach and highest risk population (could be nomads, socioeconomically disadvantaged populations, regional ethnic minorities, religious minorities, etc). | −0.275 | 0.7909 | 0.434 | 0.6773 |
| 18 | Evaluate cost-effectiveness of SMC (in terms of cost per reduction in DALYs lost due to malaria). | −0.551 | 0.5906 | 0.486 | 0.6397 |
| 19 | Develop and evaluate standardised qualitative research tools to understand challenges identified in LQAS surveys about why children were not treated in each cycle. | −1.336 | 0.1861 | −1.684 | 0.0942 |
| 20 | Investigate how prevalence of SP resistance alleles in circulating P. falciparum parasites (and their associations including quintuple and sextuple dhfr-dhps mutants) are associated with less effective parasite clearance of asymptomatic infections, protective efficacy and effectiveness of SMC. | −0.579 | 0.5715 | 0.122 | 0.9129 |
| 21 | Investigate the potential implications of expansion of the eligible age range for SMC in terms of selection of resistance alleles among circulating P. falciparum parasites. | 2.728 | 0.0054‡ | 0.104 | 0.9252 |
| 22 | Test and evaluate use of digital tools by SMC community distributors to improve quality of SMC delivery. | 1.046 | 0.3026 | −0.33 | 0.7535 |
| 23 | Develop and evaluate new techniques for malaria risk mapping for SMC planning purposes. | 0.069 | 0.9512 | 0.868 | 0.3986 |
| 24 | Analyse determinants of spatiotemporal inequalities in SMC coverage and other outcomes. | 0.937 | 0.357 | −0.243 | 0.819 |
| 25 | Develop and evaluate models to improve delivery of SMC to populations living in international border areas. | 1.13 | 0.265 | −0.851 | 0.4078 |
Rated higher among respondents not currently working in academia or research institutions.
Rated higher among Africa-based respondents.
Rated higher among respondents resident in other geographies.
AQ, amodiaquine; DALYs, disability-adjusted life years; LQAS, lot quality assurance sampling; SMC, seasonal malaria chemoprevention; SP, sulfadoxine-pyrimethamine.
Finally, online supplemental table S4 provides French and Portuguese translations of the overall top 10 research priority ranking.
Discussion
While previous work by the SMC Alliance and GDG on malaria chemotherapy has attempted to articulate research priorities for SMC,10 11 some of which are in the early stages of being addressed, this represents the opinions of narrow expert committees; to our knowledge, our study is the first attempt to reach consensus by bringing together the widest-possible group of respondents with representation of international and country-level practitioners and decision-makers in the SMC space to formulate specific actionable research aims that can be readily adapted into research initiatives over the next 5–10 years. While such consultations have been carried out for malaria elimination more generally,21 this is the first to focus specifically on SMC. This consultation sought to reach consensus on medium-term research priorities for SMC from a group of global experts; to our knowledge, this represents the first to attempt to do so. We arrived at a final ranking of research priorities, based on simple scaled ranks and reciprocal rank scores, to assess sensitivity of the final ranking to different methods. Many of the highest-ranked research priorities related to antimalarial resistance; potential ‘rebound effects’; alternative SMC medicines; and integration of SMC with other interventions, particularly vaccines. Indirectly, these research priorities may also relate to the introduction of SMC delivery to new settings. Given their absence from the top 10 research priorities identified using either method, the results suggested there was general consensus on the overall effectiveness and cost effectiveness of SMC, which have been addressed by previous studies.6 7 However, the top 10 research priorities did include those related to SMC impact in specific circumstances, including ‘Evaluate the degree to which eligible children in different transmission settings (ie, according to seasonality and attack rate) benefit from SMC programmes; evaluate differential impact in different settings’ and ‘Evaluate the impact of SMC on asymptomatic malaria infection among eligible children’ (ranked seventh and eighth based on simple scaled rank scores).
The research priorities identified are timely given the recent publication of new guidelines on SMC3 and reflect the current state-of-play of SMC, given its current widespread scale-up in areas with high seasonality of malaria transmission and low prevalence of alleles for antimalarial resistance in circulating parasites (ie, West and Central Africa).22 High-ranked priorities also reflected recent changes in WHO guidelines on SMC delivery and greater latitude for adaptation of SMC to new settings,3 and considerations about its long-term sustainability. The priorities emphasise the need to address how SMC can be integrated with other malaria interventions as part of an overall malaria control and elimination package to realise potential to expand SMC to areas with higher prevalence of antimalarial resistance and with longer high-transmission seasons.23 The research priorities identified were consistent with the research needs identified by the GDG,11 while articulating more specific research aims. However, one research gap identified by the GDG, specifically the need for ‘better understanding of the pharmacokinetics of drugs used for chemoprevention’ was absent from the final ranked list of research priorities in this study; this was due to the elimination of the research priority related to pharmacokinetics following the Wave 2 survey due to insufficient agreement on the feasibility of addressing it.
Notably, two of the top 10 research priorities identified related to malaria vaccines and the implications of integrating vaccination with SMC delivery. This reflects the recent emergence of malaria vaccination as a feasible large-scale intervention, including RTS,S,24 which has been shown to be non-inferior to SMC in preventing uncomplicated malaria. Delivering RTS,S and SMC together has the potential to achieve lower malaria incidence than either intervention alone.25 The R21/Matrix-M malaria vaccine may be particularly relevant in hard-to-reach settings where regular annual delivery of four cycles of SMC is less feasible, or as a supplement to SMC in high-transmission settings.26
Although some recent work has been undertaken by organisations represented within the SMC Alliance to address some of the research priorities identified, including evaluating use of medicines in SMC such as dihydroartemisinin-piperaquine27 28 and methods for improving delivery of AQ on Day 2 and Day 3,29 further work is needed to: (1) review the current literature relevant to each research priority identified and characterise the level of evidence provided by each study30; (2) summarise and communicate available evidence with stakeholders; (3) identify research gaps; and (4) contextualise the research priorities at the national level with key partners, such as national malaria control programmes, to operationalise them into feasible and informative research. In addition, 5 of the 25 research priorities included in the final ranking exercise showed a high proportion of respondents (>33%) agreeing or strongly agreeing that they had already been addressed despite consensus on their importance and feasibility. Consultations and reviews of existing literature, ongoing projects and awarded research grants, are required to understand the key aspects of these research priorities that are yet to be addressed and to improve uptake of existing evidence. Further efforts are also needed to improve accessibility of existing evidence to stakeholders in francophone and lusophone settings.
Differences in rankings of research priorities between Africa-based respondents and those resident in other geographies may be attributable to the former’s degree of direct experiences of implementing SMC in the field and engagement with communities. Future work may seek to understand the causes underlying differences in perceptions of SMC and malaria research priorities in general.
Strengths and limitations
While strengths of the study include the wide range of experts engaged in terms of their countries of residence, and the availability of the online surveys in multiple languages, the eDelphi method itself has limitations in that it is expert-opinion based. This study did not include community members in areas where SMC is delivered and relied on SMC Alliance members and their contacts to provide the sample of experts. Although snowball sampling may have provided a convenient methodology for rapidly gathering responses from a wide range of participants, it may have introduced bias by predominantly capturing individuals within the existing professional networks of the research team and SMC Alliance members and resulted in over-representation of particular perspectives on SMC research. In addition, although including anglophone, francophone and lusophone respondents, the initial research priorities-setting workshop only included country technical coordinators employed by Malaria Consortium from a limited range of countries where SMC is currently implemented. We noted that when new research priorities suggested by respondents during Wave 1 overlapped, these were merged and generalised in cases where they were too specific (eg, related to a specific medicine or software solution) by the researchers; while this convenience approach streamlined the online surveys, this process did not directly involve respondents. The target sample size of 50 responses was not met for each survey wave, and participants did not consistently respond in each survey wave, as evidenced by differences in sample sizes by wave; this may limit the generalisability of this study’s findings. Finally, the relatively small respondent sample achieved may have limited the statistical power to detect significant differences in research priority rankings by their characteristics.
Conclusion
Our rankings of medium-term SMC research priorities set the stage for new research initiatives in SMC over the next 5–10 years, and provide a starting point for the malaria community to focus its efforts to resolve key questions surrounding SMC. They were addressed at the SMC Alliance Annual Meeting in Abuja, Nigeria from 27 February 2024 to 29 February 2024, to operationalise national-level research priorities.31 It is hoped the results of this consultation, and the consensus it has generated, can serve as a focal point for future research planning and collaboration among SMC Alliance members and the wider malaria community including research funders. The global priorities identified will be introduced to national malaria programmes to support national-level SMC research priorities.
Although some of these research priorities are in the early stages of being addressed on an ad hoc basis by SMC Alliance members,10 it is also anticipated that a review of current evidence and ongoing projects related to each research priority, integrating a hierarchy of evidence framework to assess studies’ quality and strength of evidence,32 will be conducted in the near future and disseminated to stakeholders to facilitate research uptake and identification of research gaps. Finally, it is hoped that this eDelphi exercise can both catalyse new research and encourage uptake of existing evidence with the overall aim of improving quality of delivery, effectiveness and sustainability of SMC.
Supplementary material
Acknowledgements
We would like to thank the SMC Alliance Research Subgroup for supporting this work, and its members and other experts who took part in the priority setting exercise for generously sharing their time and knowledge. We also thank the Malaria Consortium country technical coordinators from Burkina Faso, Chad, Togo, Mozambique and Uganda who participated in the initial workshop to identify a preliminary list of research priorities.
The author is a staff member of the World Health Organization. The author alone is responsible for the views expressed in this publication and they do not necessarily represent the views, decisions or policies of the World Health Organization.
Footnotes
Funding: This study was funded by philanthropic SMC funding received by Malaria Consortium, a UK-registered independent research organisation, in support of the work of the SMC Alliance.
Provenance and peer review: Not commissioned; externally peer reviewed.
Handling editor: Helen J Surana
Patient consent for publication: Consent obtained directly from patient(s).
Ethics approval: The protocol was reviewed and approved by the Institutional Review Board of Tsinghua University (IRB Number: 20220133). Participants gave informed consent to participate in the study before taking part.
Map disclaimer: The depiction of boundaries on this map does not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. This map is provided without any warranty of any kind, either express or implied.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available upon reasonable request.
References
- 1.World Health Organization . Geneva, Switzerland: World Health Organization; 2023. World malaria report 2023. [Google Scholar]
- 2.Roca-Feltrer A, Schellenberg JRMA, Smith L, et al. A simple method for defining malaria seasonality. Malar J. 2009;8:276. doi: 10.1186/1475-2875-8-276. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.World Health Organization . Seasonal malaria chemoprevention with sulfadoxine–pyrimethamine plus amodiaquine in children: a field guide. 2nd. Geneva, Switzerland: World Health Organization; 2023. edn. [Google Scholar]
- 4.Mwaiswelo R, Ngasala B, Chaky F, et al. Dihydroartemisinin-piperaquine effectiveness for seasonal malaria chemoprevention in settings with extended seasonal malaria transmission in Tanzania. Sci Rep. 2024;14:2143. doi: 10.1038/s41598-024-52706-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.World Health Organization . Geneva, Switzerland: World Health Organization; 2012. WHO policy recommendation: seasonal malaria chemoprevention (SMC) for plasmodium falciparum malaria control in highly seasonal transmission areas of the sahel sub-region in Africa. [Google Scholar]
- 6.Meremikwu MM, Donegan S, Sinclair D, et al. Intermittent preventive treatment for malaria in children living in areas with seasonal transmission. Cochrane Database Syst Rev. 2012;2012:CD003756. doi: 10.1002/14651858.CD003756.pub4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Maiga H, Gaudart J, Sagara I, et al. Two-Year Scale-Up of Seasonal Malaria Chemoprevention Reduced Malaria Morbidity among Children in the Health District of Koutiala, Mali. Int J Environ Res Public Health . 2020;17:6639. doi: 10.3390/ijerph17186639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gilmartin C, Nonvignon J, Cairns M, et al. Seasonal malaria chemoprevention in the Sahel subregion of Africa: a cost-effectiveness and cost-savings analysis. Lancet Glob Health. 2021;9:e199–208. doi: 10.1016/S2214-109X(20)30475-7. [DOI] [PubMed] [Google Scholar]
- 9.ACCESS-SMC Partnership Effectiveness of seasonal malaria chemoprevention at scale in west and central Africa: an observational study. Lancet. 2020;396:1829–40. doi: 10.1016/S0140-6736(20)32525-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.SMC Alliance . London, United Kingdom: Malaria Consortium; 2023. From concept to scale: celebrating 10 years of seasonal malaria chemoprevention. [Google Scholar]
- 11.World Health Organization . Geneva: World Health Organization; 2023. WHO guidelines for malaria, (WHO/UCN/GMP/. 2023.01 Rev.1) [Google Scholar]
- 12.de Meyrick J. The Delphi method and health research. Health Educ. 2003;103:7–16. doi: 10.1108/09654280310459112. [DOI] [Google Scholar]
- 13.Hallowell MR, Gambatese JA. Qualitative Research: Application of the Delphi Method to CEM Research. J Constr Eng Manage. 2010;136:99–107. doi: 10.1061/(ASCE)CO.1943-7862.0000137. [DOI] [Google Scholar]
- 14.Dalkey N, Helmer O. An experimental application of the Delphi method to the use of experts. Santa Monica, California: The RAND Corporation; 1962. [Google Scholar]
- 15.Okoli C, Pawlowski SD. The Delphi method as a research tool: an example, design considerations and applications. Information & Management. 2004;42:15–29. doi: 10.1016/j.im.2003.11.002. [DOI] [Google Scholar]
- 16.Hall DA, Smith H, Heffernan E, et al. Recruiting and retaining participants in e-Delphi surveys for core outcome set development: Evaluating the COMiT’ID study. PLoS ONE. 2018;13:e0201378. doi: 10.1371/journal.pone.0201378. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Jünger S, Payne SA, Brine J, et al. Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care: Recommendations based on a methodological systematic review. Palliat Med. 2017;31:684–706. doi: 10.1177/0269216317690685. [DOI] [PubMed] [Google Scholar]
- 18.King C, Baker K, Richardson S, et al. Paediatric pneumonia research priorities in the context of COVID-19: An eDelphi study. J Glob Health. 2022;12:09001. doi: 10.7189/jogh.12.09001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.GitHub Ranking choices. 2022. [13-Jun-2024]. https://github.com/surveycto/ranking-choices/blob/master/README.md Available. Accessed.
- 20.StataCorp . College Station, TX: StataCorp LLC; 2023. Stata statistical software: release 18. [Google Scholar]
- 21.Tine R, Herrera S, Badji MA, et al. Defining operational research priorities to improve malaria control and elimination in sub-Saharan Africa: results from a country-driven research prioritization setting process. Malar J. 2023;22:219. doi: 10.1186/s12936-023-04654-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Plowe CV. Malaria chemoprevention and drug resistance: a review of the literature and policy implications. Malar J. 2022;21:104. doi: 10.1186/s12936-022-04115-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Walker PGT, Griffin JT, Ferguson NM, et al. Estimating the most efficient allocation of interventions to achieve reductions in Plasmodium falciparum malaria burden and transmission in Africa: a modelling study. Lancet Glob Health. 2016;4:e474–84. doi: 10.1016/S2214-109X(16)30073-0. [DOI] [PubMed] [Google Scholar]
- 24.Samuels AM, Ansong D, Kariuki SK, et al. Efficacy of RTS,S/AS01E malaria vaccine administered according to different full, fractional, and delayed third or early fourth dose regimens in children aged 5–17 months in Ghana and Kenya: an open-label, phase 2b, randomised controlled trial. Lancet Infect Dis. 2022;22:1329–42. doi: 10.1016/S1473-3099(22)00273-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Chandramohan D, Zongo I, Sagara I, et al. Seasonal Malaria Vaccination with or without Seasonal Malaria Chemoprevention. N Engl J Med. 2021;385:1005–17. doi: 10.1056/NEJMoa2026330. [DOI] [PubMed] [Google Scholar]
- 26.Datoo MS, Dicko A, Tinto H, et al. Safety and efficacy of malaria vaccine candidate R21/Matrix-M in African children: a multicentre, double-blind, randomised, phase 3 trial. Lancet. 2024;403:533–44. doi: 10.1016/S0140-6736(23)02511-4. [DOI] [PubMed] [Google Scholar]
- 27.Nuwa A, Baker K, Bonnington C, et al. A non-randomized controlled trial to assess the protective effect of SMC in the context of high parasite resistance in Uganda. Malar J. 2023;22:63. doi: 10.1186/s12936-023-04488-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Nuwa A, Baker K, Kajubi R, et al. Effectiveness of sulfadoxine-pyrimethamine plus amodiaquine and dihydroartemisinin-piperaquine for seasonal malaria chemoprevention in Uganda: a three-arm, open-label, non-inferiority and superiority, cluster-randomised, controlled trial. Lancet Infect Dis. 2025;25:726–36. doi: 10.1016/S1473-3099(24)00746-1. [DOI] [PubMed] [Google Scholar]
- 29.Okereke E, Smith H, Oguoma C, et al. Optimizing the role of “lead mothers” in seasonal malaria chemoprevention (SMC) campaigns: formative research in Kano State, northern Nigeria. Malar J. 2023;22:13. doi: 10.1186/s12936-023-04447-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Howick J, Chalmers I, Glasziou P, et al. Oxford, United Kingdom: Oxford Centre for Evidence-Based Medicine; 2011. The 2011 Oxford CEBM levels of evidence (introductory document) [Google Scholar]
- 31.SMC Alliance SMC alliance 2024 annual meeting (Abuja) presentation. 2024. [13-Jun-2024]. https://www.smc-alliance.org/smc-resources/smc-alliance-2024-annual-meeting-abuja-presentations Available. Accessed.
- 32.Murad MH, Asi N, Alsawas M, et al. New evidence pyramid. Evid Based Med. 2016;21:125–7. doi: 10.1136/ebmed-2016-110401. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data are available upon reasonable request.