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The Cochrane Database of Systematic... Feb 2022Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria.
OBJECTIVES
To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure?
METHODS
Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).
Topics: Child; Infant; Pregnancy; Infant, Newborn; Female; Humans; Child, Preschool; Antimalarials; Sulfadoxine; Pyrimethamine; Folic Acid Antagonists; Birth Weight; Parasitemia; Vitamins; Folic Acid; Anemia; Neural Tube Defects; Dietary Supplements; Iron; Recurrence
PubMed: 36321557
DOI: 10.1002/14651858.CD014217 -
Micromachines Oct 2021Malaria affects 228 million people worldwide each year, causing severe disease and worsening the conditions of already vulnerable populations. In this review, we explore... (Review)
Review
Malaria affects 228 million people worldwide each year, causing severe disease and worsening the conditions of already vulnerable populations. In this review, we explore how malaria has been detected in the past and how it can be detected in the future. Our primary focus is on finding new directions for low-cost diagnostic methods that unspecialized personnel can apply in situ. Through this review, we show that microfluidic devices can help pre-concentrate samples of blood infected with malaria to facilitate the diagnosis. Importantly, these devices can be made cheaply and be readily deployed in remote locations.
PubMed: 34683295
DOI: 10.3390/mi12101245 -
The Lancet. Global Health Dec 2020The burden of malaria infection in sub-Saharan Africa among school-aged children aged 5-15 years is underappreciated and represents an important source of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The burden of malaria infection in sub-Saharan Africa among school-aged children aged 5-15 years is underappreciated and represents an important source of human-to-mosquito transmission of Plasmodium falciparum. Additional interventions are needed to control and eliminate malaria. We aimed to assess whether preventive treatment of malaria might be an effective means of reducing P falciparum infection and anaemia in school-aged children and lowering parasite transmission.
METHODS
In this systematic review and two meta-analyses, we searched the online databases PubMed, Embase, Cochrane CENTRAL, and Clinicaltrials.gov for intervention studies published between Jan 1, 1990, and Dec 14, 2018. We included randomised studies that assessed the effect of antimalarial treatment among asymptomatic school-aged children aged 5-15 years in sub-Saharan Africa on prevalence of P falciparum infection and anaemia, clinical malaria, and cognitive function. We first extracted data for a study-level meta-analysis, then contacted research groups to request data for an individual participant data meta-analysis. Outcomes of interest included prevalence of P falciparum infection detected by microscopy, anaemia (study defined values or haemoglobin less than age-adjusted and sex-adjusted values), clinical malaria (infection and symptoms on the basis of study-specific definitions) during follow-up, and code transmission test scores. We assessed effects by treatment type and duration of time protected, and explored effect modification by transmission setting. For study-level meta-analysis, we calculated risk ratios for binary outcomes and standardised mean differences for continuous outcomes and pooled outcomes using fixed-effect and random-effects models. We used a hierarchical generalised linear model for meta-analysis of individual participant data. This study is registered with PROSPERO, CRD42016030197.
FINDINGS
Of 628 studies identified, 13 were eligible for the study-level meta-analysis (n=16 309). Researchers from 11 studies contributed data on at least one outcome (n=15 658) for an individual participant data meta-analysis. Interventions and study designs were highly heterogeneous; overall risk of bias was low. In the study-level meta-analysis, treatment was associated with reductions in P falciparum prevalence (risk ratio [RR] 0·27, 95% CI 0·17-0·44), anaemia (0·77, 0·65-0·91), and clinical malaria (0·40, 0·28-0·56); results for cognitive outcomes are not presented because data were only available for three trials. In our individual participant data meta-analysis, we found treatment significantly decreased P falciparum prevalence (adjusted RR [ARR] 0·46, 95% CI 0·40-0·53; p<0·0001; 15 648 individuals; 11 studies), anaemia (ARR 0·85, 0·77-0·92; p<0·0001; 15 026 individuals; 11 studies), and subsequent clinical malaria (ARR 0·50, 0·39-0·60; p<0·0001; 1815 individuals; four studies) across transmission settings. We detected a marginal effect on cognitive function in children older than 10 years (adjusted mean difference in standardised test scores 0·36, 0·01-0·71; p=0·044; 3962 individuals; five studies) although we found no significant effect when combined across all ages.
INTERPRETATION
Preventive treatment of malaria among school-aged children significantly decreases P falciparum prevalence, anaemia, and risk of subsequent clinical malaria across transmission settings. Policy makers and programme managers should consider preventive treatment of malaria to protect this age group and advance the goal of malaria elimination, while weighing these benefits against potential risks of chemoprevention.
FUNDING
US National Institutes of Health and Burroughs Wellcome Fund/ASTMH Fellowship.
Topics: Adolescent; Africa South of the Sahara; Antimalarials; Child; Child, Preschool; Humans; Malaria
PubMed: 33222799
DOI: 10.1016/S2214-109X(20)30325-9 -
Malaria Journal Sep 2023Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies. (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies.
METHODS
A systematic review and meta-analysis were conducted to assess the effectiveness of TaT strategies to reduce malaria transmission.
RESULTS
A total of 72 empirical research and 24 modelling studies were identified, mainly focused on proactive mass TaT (MTaT) and reactive case detection (RACD) in higher and lower transmission settings, respectively. Ten intervention studies compared MTaT to no MTaT and the evidence for impact on malaria incidence was weak. No intervention studies compared RACD to no RACD. Compared to passive case detection (PCD) alone, PCD + RACD using standard diagnostics increased infection detection 52.7% and 11.3% in low and very low transmission settings, respectively. Using molecular methods increased this detection of infections by 1.4- and 1.1-fold, respectively.
CONCLUSION
Results suggest MTaT is not effective for reducing transmission. By increasing case detection, surveillance data provided by RACD may indirectly reduce transmission by informing coordinated responses of intervention targeting.
Topics: Humans; Malaria
PubMed: 37661286
DOI: 10.1186/s12936-023-04670-8 -
Malaria Research and Treatment 2019Malaria is a protozoan disease caused by the species. Among the five species. Among the five and malaria are by far the most predominant and widely Malaria is one... (Review)
Review
BACKGROUND
Malaria is a protozoan disease caused by the species. Among the five species. Among the five and malaria are by far the most predominant and widely Malaria is one of the leading causes of morbidity and mortality globally, particularly in the sub-Saharan countries including Ethiopia. It is also a major obstacle to socio-economic development in the country.
METHODS
Articles were searched from PubMed, Google Scholar, and Science Direct databases. The pooled prevalence estimates were analyzed using the DerSimonian-Laird random-effects model and the possible sources of heterogeneity were evaluated through subgroup analysis, metaregression, and sensitivity analysis. Publication bias was analyzed using funnel plots and Egger's test statistics. The data management and analysis were done using STATA 15.1 version software.
RESULTS
Among 922 studies initially identified, thirty-five full-text articles fulfilled the inclusion criteria and included in the study. The combined, and malaria are by far the most predominant and widely.
CONCLUSIONS
This systematic review and meta-analysis showed a high malaria prevalence in Ethiopia. Therefore, previous prevention and control measures should be revised and/or strengthened as appropriate and new strategies should be implemented. In addition, technical, financial and material support, and coordination of the regional capacity building and logistics should be adequately implemented.
PubMed: 32089818
DOI: 10.1155/2019/7065064 -
Scientific Reports May 2023Reports of an association between ovalocytosis and protection against Plasmodium infection are inconsistent. Therefore, we aimed to synthesise the overall evidence of... (Meta-Analysis)
Meta-Analysis
Reports of an association between ovalocytosis and protection against Plasmodium infection are inconsistent. Therefore, we aimed to synthesise the overall evidence of the association between ovalocytosis and malaria infection using a meta-analysis approach. The systematic review protocol was registered with PROSPERO (CRD42023393778). A systematic literature search of the MEDLINE, Embase, Scopus, PubMed, Ovid, and ProQuest databases, from inception to 30 December 2022, was performed to retrieve studies documenting the association between ovalocytosis and Plasmodium infection. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Data synthesis included a narrative synthesis and a meta-analysis to calculate the pooled effect estimate (log odds ratios [ORs]) and 95% confidence intervals (CIs) using the random-effects model. Our database search retrieved 905 articles, 16 of which were included for data synthesis. Qualitative synthesis revealed that over half of the studies showed no association between ovalocytosis and malaria infections or severity. Furthermore, our meta-analysis demonstrated no association between ovalocytosis and Plasmodium infection (P = 0.81, log OR = 0.06, 95% CI - 0.44 to 0.19, I: 86.20%; 11 studies). In conclusion, the meta-analysis results demonstrated no association between ovalocytosis and Plasmodium infection. Hence, the role of ovalocytosis in relation to protection against Plasmodium infection or disease severity should be further investigated in larger prospective studies.
Topics: Humans; Prospective Studies; Malaria; Patient Acuity; Elliptocytosis, Hereditary
PubMed: 37137935
DOI: 10.1038/s41598-023-34170-3 -
Malaria Journal Nov 2022This review article aims to investigate the genotypic profiles of Plasmodium falciparum and Plasmodium vivax isolates collected across a wide geographic region and their... (Review)
Review
This review article aims to investigate the genotypic profiles of Plasmodium falciparum and Plasmodium vivax isolates collected across a wide geographic region and their association with resistance to anti-malarial drugs used in Indonesia. A systematic review was conducted between 1991 and date. Search engines, such as PubMed, Science Direct, and Google Scholar, were used for articles published in English and Indonesian to search the literature. Of the 471 initially identified studies, 61 were selected for 4316 P. falciparum and 1950 P. vivax individual infections. The studies included 23 molecular studies and 38 therapeutic efficacy studies. K76T was the most common pfcrt mutation. K76N (2.1%) was associated with the haplotype CVMNN. By following dihydroartemisinin-piperaquine (DHA-PPQ) therapy, the mutant pfmdr1 alleles 86Y and 1034C were selected. Low prevalence of haplotype N86Y/Y184/D1246Y pfmdr1 reduces susceptibility to AS-AQ. SNP mutation pvmdr1 Y976F reached 96.1% in Papua and East Nusa Tenggara. Polymorphism analysis in the pfdhfr gene revealed 94/111 (84.7%) double mutants S108N/C59R or S108T/A16V in Central Java. The predominant pfdhfr haplotypes (based on alleles 16, 51, 59,108, 164) found in Indonesia were ANCNI, ANCSI, ANRNI, and ANRNL. Some isolates carried A437G (35.3%) or A437G/K540E SNPs (26.5%) in pfdhps. Two novel pfdhps mutant alleles, I588F/G and K540T, were associated with six pfdhps haplotypes. The highest prevalence of pvdhfr quadruple mutation (F57L/S58R/T61M/S117T) (61.8%) was detected in Papua. In pvdhps, the only polymorphism before and after 2008 was 383G mutation with 19% prevalence. There were no mutations in the pfk13 gene reported with validated and candidate or associated k13 mutation. An increased copy number of pfpm2, associated with piperaquine resistance, was found only in cases of reinfection. Meanwhile, mutation of pvk12 and pvpm4 I165V is unlikely associated with ART and PPQ drug resistance. DHA-PPQ is still effective in treating uncomplicated falciparum and vivax malaria. Serious consideration should be given to interrupt local malaria transmission and dynamic patterns of resistance to anti-malarial drugs to modify chemotherapeutic policy treatment strategies. The presence of several changes in pfk13 in the parasite population is of concern and highlights the importance of further evaluation of parasitic ART susceptibility in Indonesia.
Topics: Plasmodium vivax; Plasmodium falciparum; Indonesia; Antimalarials; Artemisinins; Polymorphism, Single Nucleotide; Drug Resistance
PubMed: 36443817
DOI: 10.1186/s12936-022-04385-2 -
Antioxidants (Basel, Switzerland) Oct 2023Nitric oxide (NO) has been implicated in the pathology of malaria. This systematic review and meta-analysis describe the association between NO levels and malaria.... (Review)
Review
Nitric oxide (NO) has been implicated in the pathology of malaria. This systematic review and meta-analysis describe the association between NO levels and malaria. Embase, Ovid, PubMed, Scopus, and Google Scholar were searched to identify studies evaluating NO levels in malaria patients and uninfected controls. Meta-regression and subgroup analyses were conducted to discern differences in NO levels between the groups. Of the 4517 records identified, 21 studies were included in the systematic review and meta-analysis. The findings illustrated significant disparities in NO levels based on geographic location and study time frames. Despite the fluctuations, such as higher NO levels in adults compared to children, no significant differences in mean NO levels between patients and uninfected controls ( = 0.25, Hedge's g: 0.35, 95% confidence interval (CI): -0.25-0.96, : 97.39%) or between severe and non-severe malaria cases ( = 0.09, Hedge's g: 0.71, 95% CI: -0.11-1.54, : 96.07%) were detected. The systematic review and meta-analysis highlighted inconsistencies in NO levels in malaria patients. Given the high heterogeneity of the results, further studies using standardized metrics for NO measurements and focusing on biochemical pathways dictating NO responses in malaria are imperative to understand the association between NO and malaria.
PubMed: 37891947
DOI: 10.3390/antiox12101868 -
The American Journal of Tropical... Sep 2017Malaria, a major global public health problem, is mainly caused by and , and is responsible for nearly half a million deaths annually. Although malaria was not... (Meta-Analysis)
Meta-Analysis Review
Malaria, a major global public health problem, is mainly caused by and , and is responsible for nearly half a million deaths annually. Although malaria was not believed to cause severe disease, recent robust studies have proved otherwise. However, the clinical spectrum and pathogenesis of severe vivax malaria and, especially, its respiratory complications remain poorly understood. A systematic search for articles reporting respiratory complications associated with vivax malaria was performed in Lilacs, Cochrane, Scielo, Web of Science, and Medline databases irrespective of publication date. Prevalence of acute respiratory distress syndrome ARDS) and associated mortality among vivax patients were calculated from cross-sectional and longitudinal studies, whereas factors associated with mortality were calculated from data pooled from case reports and series of cases. A total of 101 studies were included (49 cross-sectional or longitudinal and 52 case reports or series of cases). Prevalence of ARDS was 2.8% and 2.2% in children and adults, respectively, with nearly 50% mortality. Moreover, female sex ( = 0.013), having any comorbidity ( = 0.036), lower body temperature ( = 0.032), lower hemoglobin ( = 0.043), and oxygen saturation ( = 0.053) values were significantly associated with mortality. malaria respiratory complications included ARDS and were associated with high mortality. Demographics and clinical characteristics upon presentation to hospital were associated with mortality among patients with respiratory complications in vivax malaria. This study reaffirms the evidence of severe and fatal complications of malaria and its associated respiratory complications.
Topics: Global Health; Humans; Malaria, Vivax; Respiratory Tract Diseases
PubMed: 28722625
DOI: 10.4269/ajtmh.17-0131 -
The Cochrane Database of Systematic... Aug 2023Insecticide-based interventions, such as long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS), remain the backbone of malaria vector control.... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Insecticide-based interventions, such as long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS), remain the backbone of malaria vector control. These interventions target mosquitoes that prefer to feed and rest indoors, but have limited capacity to prevent transmission that occurs outdoors or outside regular sleeping hours. In low-endemicity areas, malaria elimination will require that these control gaps are addressed, and complementary tools are found. The use of topical repellents may be particularly useful for populations who may not benefit from programmatic malaria control measures, such as refugees, the military, or forest goers. This Cochrane Review aims to measure the effectiveness of topical repellents to prevent malaria infection among high- and non-high-risk populations living in malaria-endemic regions.
OBJECTIVES
To assess the effect of topical repellents alone or in combination with other background interventions (long-lasting insecticide-treated nets, or indoor residual spraying, or both) for reducing the incidence of malaria in high- and non-high-risk populations living in endemic areas.
SEARCH METHODS
We searched the following databases up to 11 January 2023: the Cochrane Infectious Diseases Group Specialised Register; CENTRAL (in the Cochrane Library); MEDLINE; Embase; CAB Abstracts; and LILACS. We also searched trial registration platforms and conference proceedings; and contacted organizations and companies for ongoing and unpublished trials.
SELECTION CRITERIA
We included randomized controlled trials (RCTs) and cluster-randomized controlled trials (cRCTs) of topical repellents proven to repel mosquitoes. We also included non-randomized studies that complied with pre-specified inclusion criteria: controlled before-after studies (CBA), controlled interrupted time series (ITS), and controlled cross-over trials.
DATA COLLECTION AND ANALYSIS
Four review authors independently assessed trials for inclusion, and extracted the data. Two authors independently assessed the risk of bias (RoB) using the Cochrane RoB 2 tool. A fifth review author resolved any disagreements. We analysed data by conducting a meta-analysis, stratified by whether studies included populations considered to be at high-risk of developing malaria infection (for example, refugees, forest goers, or deployed military troops). We combined results from cRCTs with RCTs by adjusting for clustering and presented results using forest plots. We used the GRADE framework to assess the certainty of the evidence. We only included data on Plasmodium falciparum infections in the meta-analysis.
MAIN RESULTS
Thirteen articles relating to eight trials met the inclusion criteria and were qualitatively described. We included six trials in the meta-analysis (five cRCTs and one RCT). Effect on malaria incidence Topical repellents may slightly reduce P falciparum infection and clinical incidence when both outcomes are considered together (incidence rate ratio (IRR) 0.74, 95% confidence interval (CI) 0.56 to 0.98; 3 cRCTs and 1 RCT, 61,651 participants; low-certainty evidence); but not when these two outcomes were considered independently. Two cRCTs and one RCT (12,813 participants) evaluated the effect of topical repellents on infection incidence (IRR 0.76, 95% CI 0.56 to 1.02; low-certainty evidence). One cRCT (48,838 participants) evaluated their effect on clinical case incidence (IRR 0.66, 95% CI 0.32 to 1.36; low-certainty evidence). Three studies (2 cRCTs and 1 RCT) included participants belonging to groups considered at high-risk of being infected, while only one cRCT did not include participants at high risk. Adverse events Topical repellents are considered safe. The prevalence of adverse events among participants who used topical repellents was very low (0.6%, 283/47,515) and limited to mild skin reactions. Effect on malaria prevalence Topical repellents may slightly reduce P falciparum prevalence (odds ratio (OR) 0.81, 95% CI 0.67 to 0.97; 3 cRCTs and 1 RCT; 55,366 participants; low-certainty evidence). Two of these studies (1 cRCT and 1 RCT) were carried out in refugee camps, and included exclusively high-risk populations that were not receiving any other background vector control intervention.
AUTHORS' CONCLUSIONS
There is insufficient evidence to conclude that topical repellents can prevent malaria in settings where other vector control interventions are in place. We found the certainty of evidence for all outcomes to be low, primarily due to the risk of bias. A protective effect was suggested among high-risk populations, specially refugees, who might not have access to other standard vector control measures. More adequately powered clinical trials carried out in refugee camps could provide further information on the potential benefit of topical repellents in this setting. Individually randomized studies are also likely necessary to understand whether topical repellents have an effect on personal protection, and the degree to which diversion to non-protected participants affects overall transmission dynamics. Despite this, the potential additional benefits of topical repellents are most likely limited in contexts where other interventions are available.
Topics: Animals; Humans; Insecticides; Mosquito Vectors; Malaria, Falciparum; Controlled Before-After Studies; Culicidae
PubMed: 37602418
DOI: 10.1002/14651858.CD015422.pub2