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Malaria Journal May 2023Understanding malaria epidemiology is a critical step toward efficient malaria control and elimination. The objective of this meta-analysis was to derive robust... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Understanding malaria epidemiology is a critical step toward efficient malaria control and elimination. The objective of this meta-analysis was to derive robust estimates of malaria prevalence and Plasmodium species from studies conducted in Mauritania and published since 2000.
METHODS
The present review followed the PRISMA guidelines. Searches were conducted in various electronic databases such as PubMed, Web of Science, and Scopus. To obtain pooled prevalence of malaria, meta-analysis was performed using the DerSimonian-Laird random-effects model. Methodological quality of eligible prevalence studies was assessed using Joanna Briggs Institute tool. Inconsistency and heterogeneity between studies were quantified by the I index and Cochran's Q test. Publication bias was assessed with funnel plots and Egger's regression tests.
RESULTS
A total of 16 studies with a good individual methodological quality were included and analysed in this study. The overall random effects pooled prevalence of malaria infection (symptomatic and asymptomatic) across all included studies was 14.9% (95% confidence interval [95% CI]: 6.64, 25.80, I = 99.8%, P < 0.0001) by microscopy, 25.6% (95% CI: 8.74, 47.62, I = 99.6%, P < 0.0001) by PCR and 24.3% (95% CI: 12.05 to 39.14, I = 99.7%, P < 0.0001) by rapid diagnostic test. Using microscopy, the prevalence of asymptomatic malaria was 1.0% (95% CI: 0.00, 3.48) against 21.46% (95% CI: 11.03, 34.21) in symptomatic malaria. The overall prevalence of Plasmodium falciparum and Plasmodium vivax was 51.14% and 37.55%, respectively. Subgroup analysis showed significant variation (P = 0.039) in the prevalence of malaria between asymptomatic and symptomatic cases.
CONCLUSION
Plasmodium falciparum and P. vivax are widespread in Mauritania. Results of this meta-analysis implies that distinct intervention measures including accurate parasite-based diagnosis and appropriate treatment of confirmed malaria cases are critical for a successful malaria control and elimination programme in Mauritania.
Topics: Humans; Prevalence; Mauritania; Malaria; Malaria, Vivax; Plasmodium; Plasmodium vivax; Plasmodium falciparum; Malaria, Falciparum
PubMed: 37131226
DOI: 10.1186/s12936-023-04569-4 -
Heliyon Apr 2023Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to...
Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to conduct a systematic review and meta-analysis on malaria prevalence in Pakistan from 2006 to 2021. We searched PubMed, Science Direct, EMBASE, EMCare, and Google Scholar to acquire data on the prevalence of malaria infections. We performed a meta-analysis with a random-effects model to obtain the pooled prevalence of malaria, Plasmodium vivax, and Plasmodium falciparum. Meta-analysis was computed using R 4.1.2 Version statistical software. I and time series analysis were performed to identify a possible source of heterogeneity across studies. A funnel plot and the Freeman-Tukey Double Arcsine Transformed Proportion were used to evaluate the presence of publication bias. Out of the 315 studies collected, only 45 full-text articles were screened and included in the final measurable meta-analysis. Pooled malaria prevalence in Pakistan was 23.3%, with , , and mixed infection rates of 79.13%, 16.29%, and 3.98%, respectively. Similarly, the analysis revealed that the maximum malaria prevalence was 99.79% in Karachi and the minimum was 1.68% in the Larkana district. Amazingly, this systematic review and meta-analysis detected a wide variation in malaria prevalence in Pakistan. Pakistan's public health department and other competent authorities should pay close attention to the large decrease in mosquito populations to curb the infection rate.
PubMed: 37123939
DOI: 10.1016/j.heliyon.2023.e15373 -
The Lancet. Global Health Apr 2023Humanitarian emergencies can lead to population displacement, food insecurity, severe health system disruptions, and malaria epidemics among individuals who are... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Humanitarian emergencies can lead to population displacement, food insecurity, severe health system disruptions, and malaria epidemics among individuals who are immunologically naive. We aimed to assess the impact of different vector control interventions on malaria disease burden during humanitarian emergencies.
METHODS
In this systematic review and meta-analysis, we searched ten electronic databases and two clinical trial registries from database inception to Oct 19, 2020, with no restrictions on language or study design. We also searched grey literature from 59 stakeholders. Studies were eligible if the population was affected by a humanitarian emergency in a malaria endemic region. We included studies assessing any vector control intervention and in which the primary outcome of interest was malaria infection risk. Reviewers (LAM, JF-A, KC, BP, and LP) independently extracted information from eligible studies, without masking of author or publication, into a database. We did random-effects meta-analyses to calculate pooled risk ratios (RRs) for randomised controlled trials, odds ratios (ORs) for dichotomous outcomes, and incidence rate ratios (IRR) for clinical malaria in non-randomised studies. Certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. This study is registered with PROSPERO, CRD42020214961.
FINDINGS
Of 12 475 studies screened, 22 studies were eligible for inclusion in our meta-analysis. All studies were conducted between Sept 1, 1989, and Dec 31, 2018, in chronic emergencies, with 616 611 participants from nine countries, evaluating seven different vector control interventions. Insecticide-treated nets significantly decreased Plasmodium falciparum incidence (RR 0·55 [95% CI 0·37-0·79]; high certainty) and Plasmodium vivax incidence (RR 0·69 [0·51-0·94]; high certainty). Evidence for an effect of indoor residual spraying on P falciparum (IRR 0·57 [95% CI 0·53-0·61]) and P vivax (IRR 0·51 [0·49-0·52]) incidence was of very low certainty. Topical repellents were associated with reductions in malaria infection (RR 0·58 [0·35-0·97]; moderate certainty). Moderate-to-high certainty evidence for an effect of insecticide-treated chaddars (equivalent to shawls or blankets) and insecticide-treated cattle on malaria outcomes was evident in some emergency settings. There was very low certainty evidence for the effect of insecticide-treated clothing.
INTERPRETATION
Study findings strengthen and support WHO policy recommendations to deploy insecticide-treated nets during chronic humanitarian emergencies. There is an urgent need to evaluate and adopt novel interventions for malaria control in the acute phase of humanitarian emergencies.
FUNDING
WHO Global Malaria Programme.
Topics: Humans; Animals; Cattle; Insecticides; Emergencies; Malaria; Malaria, Falciparum; Plasmodium falciparum
PubMed: 36925174
DOI: 10.1016/S2214-109X(23)00044-X -
European Journal of Pharmaceutical... Apr 2023Malaria poses a severe public health risk and a significant economic burden in disease-endemic countries. One of the most severe issues in malaria control is the... (Review)
Review
Malaria poses a severe public health risk and a significant economic burden in disease-endemic countries. One of the most severe issues in malaria control is the development of drug resistance in malaria parasites. The standard treatment for malaria is artemisinin-combination therapy (ACT). Nevertheless, the Plasmodium parasite's extensive resistance to prior drugs and reduced ACT efficiency necessitates novel drug discovery. The progress in discovering novel, affordable, and effective antimalarial agents is significant in combating drug resistance, and the hybrid drug concept can be used to covalently link two or more active pharmacophores that may act on multiple targets. Pyrazole and pyrazoline derivatives are considered pharmacologically necessary active heterocyclic scaffolds that possess almost all types of pharmacological activities. This review summarized recent progress in antimalarial activities of synthesized pyrazole and pyrazoline derivatives. The studies published since 2000 are included in this systematic review. This review is anticipated to be beneficial for future study and new ideas in searching for rational development strategies for more effective pyrazole and pyrazoline derivatives as antimalarial drugs.
Topics: Humans; Antimalarials; Malaria; Pyrazoles; Drug Resistance; Folic Acid Antagonists; Plasmodium falciparum
PubMed: 36563914
DOI: 10.1016/j.ejps.2022.106365 -
The American Journal of Tropical... Jan 2023The five major Plasmodium spp. that cause human malaria appear similar under light microscopy, which raises the possibility that misdiagnosis could routinely occur in... (Meta-Analysis)
Meta-Analysis
The five major Plasmodium spp. that cause human malaria appear similar under light microscopy, which raises the possibility that misdiagnosis could routinely occur in clinical settings. Assessing the extent of misdiagnosis is of particular importance for monitoring P. knowlesi, which cocirculates with the other Plasmodium spp. We performed a systematic review and meta-analysis of studies comparing the performance of microscopy and polymerase chain reaction (PCR) for diagnosing malaria in settings with co-circulation of the five Plasmodium spp. We assessed the extent to which co-circulation of Plasmodium parasites affects diagnostic outcomes. We fit a Bayesian hierarchical latent class model to estimate variation in microscopy sensitivity and specificity measured against PCR as the gold standard. Mean sensitivity of microscopy was low, yet highly variable across Plasmodium spp., ranging from 65.7% (95% confidence interval: 48.1-80.3%) for P. falciparum to 0.525% (95% confidence interval 0.0210-3.11%) for P. ovale. Observed PCR prevalence was positively correlated with estimated microscopic sensitivity and negatively correlated with estimated microscopic specificity, though the strength of the associations varied by species. Our analysis suggests that cocirculation of Plasmodium spp. undermines the accuracy of microscopy. Sensitivity was considerably lower for P. knowlesi, P. malariae, and P. ovale. The negative association between specificity and prevalence imply that less frequently encountered species may be misdiagnosed as more frequently encountered species. Together, these results suggest that the burden of P. knowlesi, P. malariae, and P. ovale may be underappreciated in a clinical setting.
Topics: Humans; Bayes Theorem; Malaria; Malaria, Falciparum; Microscopy; Plasmodium knowlesi; Polymerase Chain Reaction; Communicable Diseases, Emerging; Coinfection; Diagnostic Errors; Plasmodium ovale; Plasmodium malariae
PubMed: 36509046
DOI: 10.4269/ajtmh.21-1155 -
Parasites & Vectors Dec 2022The production of Plasmodium gametocytes in vitro is a real challenge. Many protocols have been described, but few have resulted in the production of viable and... (Review)
Review
BACKGROUND
The production of Plasmodium gametocytes in vitro is a real challenge. Many protocols have been described, but few have resulted in the production of viable and infectious gametocytes in sufficient quantities to conduct research on-but not limited to-transmission-blocking drug and vaccine development. The aim of this review was to identify and discuss gametocyte production protocols that have been developed over the last two decades.
METHODS
We analyzed the original gametocyte production protocols published from 2000 onwards based on a literature search and a thorough review. A systematic review was performed of relevant articles identified in the PubMed, Web of Sciences and ScienceDirect databases.
RESULTS
A total 23 studies on the production of Plasmodium gametocytes were identified, 19 involving in vitro Plasmodium falciparum, one involving Plasmodium knowlesi and three involving ex vivo Plasmodium vivax. Of the in vitro studies, 90% used environmental stressors to trigger gametocytogenesis. Mature gametocytemia of up to 4% was reported.
CONCLUSIONS
Several biological parameters contribute to an optimal production in vitro of viable and infectious mature gametocytes. The knowledge gained from this systematic review on the molecular mechanisms involved in gametocytogenesis enables reproducible gametocyte protocols with transgenic parasite lines to be set up. This review highlights the need for additional gametocyte production protocols for Plasmodium species other than P. falciparum.
Topics: Humans; Malaria, Falciparum; Plasmodium falciparum; Plasmodium knowlesi; Plasmodium vivax; Systematic Reviews as Topic
PubMed: 36471426
DOI: 10.1186/s13071-022-05566-3 -
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 -
Lancet (London, England) Jan 2023Malaria in the first trimester of pregnancy is associated with adverse pregnancy outcomes. Artemisinin-based combination therapies (ACTs) are a highly effective,... (Meta-Analysis)
Meta-Analysis
Pregnancy outcomes after first-trimester treatment with artemisinin derivatives versus non-artemisinin antimalarials: a systematic review and individual patient data meta-analysis.
BACKGROUND
Malaria in the first trimester of pregnancy is associated with adverse pregnancy outcomes. Artemisinin-based combination therapies (ACTs) are a highly effective, first-line treatment for uncomplicated Plasmodium falciparum malaria, except in the first trimester of pregnancy, when quinine with clindamycin is recommended due to concerns about the potential embryotoxicity of artemisinins. We compared adverse pregnancy outcomes after artemisinin-based treatment (ABT) versus non-ABTs in the first trimester of pregnancy.
METHODS
For this systematic review and individual patient data (IPD) meta-analysis, we searched MEDLINE, Embase, and the Malaria in Pregnancy Library for prospective cohort studies published between Nov 1, 2015, and Dec 21, 2021, containing data on outcomes of pregnancies exposed to ABT and non-ABT in the first trimester. The results of this search were added to those of a previous systematic review that included publications published up until November, 2015. We included pregnancies enrolled before the pregnancy outcome was known. We excluded pregnancies with missing estimated gestational age or exposure information, multiple gestation pregnancies, and if the fetus was confirmed to be unviable before antimalarial treatment. The primary endpoint was adverse pregnancy outcome, defined as a composite of either miscarriage, stillbirth, or major congenital anomalies. A one-stage IPD meta-analysis was done by use of shared-frailty Cox models. This study is registered with PROSPERO, number CRD42015032371.
FINDINGS
We identified seven eligible studies that included 12 cohorts. All 12 cohorts contributed IPD, including 34 178 pregnancies, 737 with confirmed first-trimester exposure to ABTs and 1076 with confirmed first-trimester exposure to non-ABTs. Adverse pregnancy outcomes occurred in 42 (5·7%) of 736 ABT-exposed pregnancies compared with 96 (8·9%) of 1074 non-ABT-exposed pregnancies in the first trimester (adjusted hazard ratio [aHR] 0·71, 95% CI 0·49-1·03). Similar results were seen for the individual components of miscarriage (aHR=0·74, 0·47-1·17), stillbirth (aHR=0·71, 0·32-1·57), and major congenital anomalies (aHR=0·60, 0·13-2·87). The risk of adverse pregnancy outcomes was lower with artemether-lumefantrine than with oral quinine in the first trimester of pregnancy (25 [4·8%] of 524 vs 84 [9·2%] of 915; aHR 0·58, 0·36-0·92).
INTERPRETATION
We found no evidence of embryotoxicity or teratogenicity based on the risk of miscarriage, stillbirth, or major congenital anomalies associated with ABT during the first trimester of pregnancy. Given that treatment with artemether-lumefantrine was associated with fewer adverse pregnancy outcomes than quinine, and because of the known superior tolerability and antimalarial effectiveness of ACTs, artemether-lumefantrine should be considered the preferred treatment for uncomplicated P falciparum malaria in the first trimester. If artemether-lumefantrine is unavailable, other ACTs (except artesunate-sulfadoxine-pyrimethamine) should be preferred to quinine. Continued active pharmacovigilance is warranted.
FUNDING
Medicines for Malaria Venture, WHO, and the Worldwide Antimalarial Resistance Network funded by the Bill & Melinda Gates Foundation.
Topics: Female; Pregnancy; Humans; Antimalarials; Pregnancy Outcome; Quinine; Pregnancy Trimester, First; Abortion, Spontaneous; Stillbirth; Prospective Studies; Artemether; Artemether, Lumefantrine Drug Combination; Malaria, Falciparum; Malaria; Drug Combinations; Ethanolamines
PubMed: 36442488
DOI: 10.1016/S0140-6736(22)01881-5 -
Photodiagnosis and Photodynamic Therapy Dec 2022Machine and deep learning techniques are prevalent in the medical discipline due to their high level of accuracy in disease diagnosis. One such disease is malaria caused... (Review)
Review
Machine and deep learning techniques are prevalent in the medical discipline due to their high level of accuracy in disease diagnosis. One such disease is malaria caused by Plasmodium falciparum and transmitted by the female anopheles mosquito. According to the World Health Organisation (WHO), millions of people are infected annually, leading to inevitable deaths in the infected population. Statistical records show that early detection of malaria parasites could prevent deaths and machine learning (ML) has proved helpful in the early detection of malarial parasites. Human error is identified to be a major cause of inaccurate diagnostics in the traditional microscopy malaria diagnosis method. Therefore, the method would be more reliable if human expert dependency is restricted or entirely removed, and thus, the motivation of this paper. This study presents a systematic review to understand the prevalent machine learning algorithms applied to a low-cost, portable optical microscope in the automation of blood film interpretation for malaria parasite detection. Peer-reviewed papers were downloaded from selected reputable databases eg. Elsevier, IEEExplore, Pubmed, Scopus, Web of Science, etc. The extant literature suggests that convolutional neural network (CNN) and its variants (deep learning) account for 41.9% of the microscopy malaria diagnosis using machine learning with a prediction accuracy of 99.23%. Thus, the findings suggest that early detection of the malaria parasite has improved through the application of CNN and other ML algorithms on microscopic malaria parasite detection.
Topics: Animals; Female; Humans; Malaria, Falciparum; Microscopy; Deep Learning; Photochemotherapy; Malaria; Plasmodium
PubMed: 36379305
DOI: 10.1016/j.pdpdt.2022.103198 -
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