Public stewardship of private for-profit healthcare providers in low- and middle-income countries.

Governments use different approaches to ensure that private for-profit healthcare services meet certain quality standards. Such government guidance, referred to as public stewardship, encompasses government policies, regulatory mechanisms, and implementation strategies for ensuring accountability in the delivery of services. However, the effectiveness of these strategies in low- and middle-income countries (LMICs) have not been the subject of a systematic review. To assess the effects of public sector regulation, training, or co-ordination of the private for-profit health sector in low- and middle-income countries. For related systematic reviews, we searched the Cochrane Database of Systematic Reviews (CDSR) 2015, Issue 4; Database of Abstracts of Reviews of Effectiveness (DARE) 2015, Issue 1; Health Technology Assessment Database (HTA) 2015, Issue 1; all part of The Cochrane Library, and searched 28 April 2015. For primary studies, we searched MEDLINE, Epub Ahead of Print, In-Process & Other Non-Indexed Citations, MEDLINE Daily and MEDLINE 1946 to Present, OvidSP (searched 16 June 2016); Science Citation Index and Social Sciences Citation Index 1987 to present, and Emerging Sources Citation Index 2015 to present, ISI Web of Science (searched 3 May 2016 for papers citing included studies); Cochrane Central Register of Controlled Trials (CENTRAL), 2015, Issue 3, part of The Cochrane Library (including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register) (searched 28 April 2015); Embase 1980 to 2015 Week 17, OvidSP (searched 28 April 2015); Global Health 1973 to 2015 Week 16, OvidSP (searched 30 April 2015); WHOLIS, WHO (searched 30 April 2015); Science Citation Index and Social Sciences Citation Index 1975 to present, ISI Web of Science (searched 30 April 2015); Health Management, ProQuest (searched 22 November 2013). In addition, in April 2016, we searched the reference lists of relevant articles, WHO International Clinical Trials Registry Platform, Clinicaltrials.gov, and various electronic databases of grey literature. Randomised trials, non-randomised trials, interrupted time series studies, or controlled before-after studies. Two authors independently assessed study eligibility and extracted data, comparing their results and resolving discrepancies by consensus. We expressed study results as risk ratios (RR) or mean differences (MD) with 95% confidence intervals (CI), where appropriate, and assessed the certainty of the evidence using Grades of Recommendation, Assessment, Development and Evaluation (GRADE). We did not conduct meta-analysis because of heterogeneity of interventions and study designs. We identified 20,177 records, 50 of them potentially eligible. We excluded 39 potentially eligible studies because they did not involve a rigorous evaluation of training, regulation, or co-ordination of private for-profit healthcare providers in LMICs; five studies identified after the review was submitted are awaiting assessment; and six studies met our inclusion criteria. Two included studies assessed training alone; one assessed regulation alone; three assessed a multifaceted intervention involving training and regulation; and none assessed co-ordination. All six included studies targeted private for-profit pharmacy workers in Africa and Asia.Three studies found that training probably increases sale of oral rehydration solution (one trial in Kenya, 106 pharmacies: RR 3.04, 95% CI 1.37 to 6.75; and one trial in Indonesia, 87 pharmacies: RR 1.41, 95% CI 1.03 to 1.93) and dispensing of anti-malarial drugs (one trial in Kenya, 293 pharmacies: RR 8.76, 95% CI 0.94 to 81.81); moderate-certainty evidence.One study conducted in the Lao People's Democratic Republic shows that regulation of the distribution and sale of registered pharmaceutical products may improve composite pharmacy indicators (one trial, 115 pharmacies: improvements in four of six pharmacy indicators; low-certainty evidence).The outcome in three multifaceted intervention studies was the quality of pharmacy practice; including the ability to ask questions, give advice, and provide appropriate treatment. The trials applied regulation, training, and peer influence in sequence; and the study design does not permit separation of the effects of the different interventions. Two trials conducted among 136 pharmacies in Vietnam found that the multifaceted intervention may improve the quality of pharmacy practice; but the third study, involving 146 pharmacies in Vietnam and Thailand, found that the intervention may have little or no effects on the quality of pharmacy practice (low-certainty evidence).Only two studies (both conducted in Vietnam) reported cost data, with no rigorous assessment of the economic implications of implementing the interventions in resource-constrained settings. No study reported data on equity, mortality, morbidity, adverse effects, satisfaction, or attitudes. Training probably improves quality of care (i.e. adherence to recommended practice), regulation may improve quality of care, and we are uncertain about the effects of co-ordination on quality of private for-profit healthcare services in LMICs. The likelihood that further research will find the effect of training to be substantially different from the results of this review is moderate; implying that monitoring of the impact is likely to be needed if training is implemented. The low certainty of the evidence for regulation implies that the likelihood of further research finding the effect of regulation to be substantially different from the results of this review is high. Therefore, an impact evaluation is warranted if government regulation of private for-profit providers is implemented in LMICs. Rigorous evaluations of these interventions should also assess other outcomes such as impacts on equity, cost implications, mortality, morbidity, and adverse effects.

Wiysonge CS ，Abdullahi LH ，Ndze VN ，Hussey GD ... -  《Cochrane Database of Systematic Reviews》

Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.

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. 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? 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).

Crider K ，Williams J ，Qi YP ，Gutman J ，Yeung L ，Mai C ，Finkelstain J ，Mehta S ，Pons-Duran C ，Menéndez C ，Moraleda C ，Rogers L ，Daniels K ，Green P ... -  《Cochrane Database of Systematic Reviews》

Interventions for improving coverage of childhood immunisation in low- and middle-income countries.

Immunisation is a powerful public health strategy for improving child survival, not only by directly combating key diseases that kill children but also by providing a platform for other health services. However, each year millions of children worldwide, mostly from low- and middle-income countries (LMICs), do not receive the full series of vaccines on their national routine immunisation schedule. This is an update of the Cochrane review published in 2011 and focuses on interventions for improving childhood immunisation coverage in LMICs. To evaluate the effectiveness of intervention strategies to boost and sustain high childhood immunisation coverage in LMICs. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) 2016, Issue 4, part of The Cochrane Library. www.cochranelibrary.com, including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register (searched 12 May 2016); MEDLINE In-Process and Other Non-Indexed Citations, MEDLINE Daily and MEDLINE 1946 to Present, OvidSP (searched 12 May 2016); CINAHL 1981 to present, EbscoHost (searched 12 May 2016); Embase 1980 to 2014 Week 34, OvidSP (searched 2 September 2014); LILACS, VHL (searched 2 September 2014); Sociological Abstracts 1952 - current, ProQuest (searched 2 September 2014). We did a citation search for all included studies in Science Citation Index and Social Sciences Citation Index, 1975 to present; Emerging Sources Citation Index 2015 to present, ISI Web of Science (searched 2 July 2016). We also searched the two Trials Registries: ICTRP and ClinicalTrials.gov (searched 5 July 2016) SELECTION CRITERIA: Eligible studies were randomised controlled trials (RCT), non-RCTs, controlled before-after studies, and interrupted time series conducted in LMICs involving children aged from birth to four years, caregivers, and healthcare providers. We independently screened the search output, reviewed full texts of potentially eligible articles, assessed risk of bias, and extracted data in duplicate; resolving discrepancies by consensus. We then conducted random-effects meta-analyses and used GRADE to assess the certainty of evidence. Fourteen studies (10 cluster RCTs and four individual RCTs) met our inclusion criteria. These were conducted in Georgia (one study), Ghana (one study), Honduras (one study), India (two studies), Mali (one study), Mexico (one study), Nicaragua (one study), Nepal (one study), Pakistan (four studies), and Zimbabwe (one study). One study had an unclear risk of bias, and 13 had high risk of bias. The interventions evaluated in the studies included community-based health education (three studies), facility-based health education (three studies), household incentives (three studies), regular immunisation outreach sessions (one study), home visits (one study), supportive supervision (one study), information campaigns (one study), and integration of immunisation services with intermittent preventive treatment of malaria (one study).We found moderate-certainty evidence that health education at village meetings or at home probably improves coverage with three doses of diphtheria-tetanus-pertussis vaccines (DTP3: risk ratio (RR) 1.68, 95% confidence interval (CI) 1.09 to 2.59). We also found low-certainty evidence that facility-based health education plus redesigned vaccination reminder cards may improve DTP3 coverage (RR 1.50, 95% CI 1.21 to 1.87). Household monetary incentives may have little or no effect on full immunisation coverage (RR 1.05, 95% CI 0.90 to 1.23, low-certainty evidence). Regular immunisation outreach may improve full immunisation coverage (RR 3.09, 95% CI 1.69 to 5.67, low-certainty evidence) which may substantially improve if combined with household incentives (RR 6.66, 95% CI 3.93 to 11.28, low-certainty evidence). Home visits to identify non-vaccinated children and refer them to health clinics may improve uptake of three doses of oral polio vaccine (RR 1.22, 95% CI 1.07 to 1.39, low-certainty evidence). There was low-certainty evidence that integration of immunisation with other services may improve DTP3 coverage (RR 1.92, 95% CI 1.42 to 2.59). Providing parents and other community members with information on immunisation, health education at facilities in combination with redesigned immunisation reminder cards, regular immunisation outreach with and without household incentives, home visits, and integration of immunisation with other services may improve childhood immunisation coverage in LMIC. Most of the evidence was of low certainty, which implies a high likelihood that the true effect of the interventions will be substantially different. There is thus a need for further well-conducted RCTs to assess the effects of interventions for improving childhood immunisation coverage in LMICs.

Oyo-Ita A ，Wiysonge CS ，Oringanje C ，Nwachukwu CE ，Oduwole O ，Meremikwu MM ... -  《Cochrane Database of Systematic Reviews》

Subsidising artemisinin-based combination therapy in the private retail sector.

Malaria causes ill health and death in Africa. Treating illness promptly with artemisinin-based combination therapy (ACT) is likely to cure people and avoid the disease progressing to more severe forms and death. In many countries, ACT use remains low. Part of the problem is that most people seek treatment from the retail sector where ACTs are expensive; this expense is a barrier to their use.The Global Fund and other international organisations are subsidising the cost of ACTs for private retail providers to improve access to ACTs. The subsidy was initially organised through a stand-alone initiative, called the Affordable Medicines Facility-malaria (AMFm), but has since been integrated into the Global Fund core grant management and financial processes. To assess the effect of programmes that include ACT price subsidies for private retailers on ACT use, availability, price and market share. We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2015, Issue 1, The Cochrane Library, including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register); MEDLINE (OvidSP), EMBASE (OvidSP), CINAHL (EbscoHost), EconLit (ProQuest), Global Health (OvidSP), Regional Indexes (Global Health Library, WHO), LILACS (Global Health Library, WHO), Science Citation Index and Social Sciences Citation Index (ISI Web of Science) and Health Management (ProQuest). All databases were searched February 2015, except for Health Management which was searched November 2013, without any date, language or publication status restrictions. We also searched the International Clinical Trials Registry Platform (ICTRP; WHO), ClinicalTrials.gov (NIH) and various grey literature sources. We also conducted a cited reference search for all included studies in ISI Web of Knowledge, checked references of identified articles and contacted authors to identify additional studies. Randomised trials, non-randomised trials, controlled before-after studies and interrupted-time-series studies that compared the effects of ACT price subsidies for private retailers to no subsidies or alternative ACT financing mechanisms were eligible for inclusion. Two authors independently screened and selected studies for inclusion. Two review authors independently extracted data, assessed study risk of bias and confidence in effect estimates (certainty of evidence) using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). We included four trials (two cluster-randomised trials reported in three articles and two non-randomised cluster trials). Three trials assessed retail sector ACT subsidies combined with supportive interventions (retail outlet provider training, community awareness and mass media campaigns). One trial assessed vouchers provided to households to purchase subsidised ACTs. Price subsidies ranged from 80% to 95%. One trial enrolled children under five years of age; the other three trials studied people of all age groups. The studies were done in rural districts in East Africa (Kenya, Uganda and Tanzania).In this East Africa setting, these ACT subsidy programmes increased the percentage of children under five years of age receiving ACTs on the day, or following day, of fever onset by 25 percentage points (95% confidence interval (CI) 14.1 to 35.9 percentage points; 1 study, high certainty evidence). This suggests that in practice, among febrile children under five years of age with an ACT usage rate of 5% without a subsidy, subsidy programmes would increase usage by between 19% and 41% over a one year period.The ACT subsidy programmes increased the percentage of retail outlets stocking ACTs for children under five years of age by 31.9 percentage points (95% CI 26.3 to 37.5 percentage points; 1 study, high certainty evidence). Effects on ACT stocking for patients of any age is unknown because the certainty of evidence was very low.The ACT subsidy programmes decreased the median cost of ACTs for children under five years of age by US$ 0.84 (median cost per ACT course without subsidy: US$ 1.08 versus with subsidy: US$ 0.24; 1 study, high certainty evidence).The ACT subsidy programmes increased the market share of ACTs for children under five years of age by between 23.6 and 63.0 percentage points (1 study, high certainty evidence).The ACT subsidy programmes decreased the use of older antimalarial drugs (such as amodiaquine and sulphadoxine-pyrimethamine) among children under five years of age by 10.4 percentage points (95% CI 3.9 to 16.9 percentage points; 1 study, high certainty evidence).None of the three studies of ACT subsidies reported the number of patients treated who had confirmed malaria.Vouchers increased the likelihood that an illness is treated with an ACT by 16 to 23 percentage points; however, vouchers were associated with a high rate of over-treatment of malaria (only 56% of patients taking ACTs from the drug shop tested positive for malaria under the 92% subsidy; 1 study, high certainty evidence). Programmes that include substantive subsidies for private sector retailers combined with training of providers and social marketing improved use and availability of ACTs for children under five years of age with suspected malaria in research studies from three countries in East Africa. These programmes also reduced prices of ACTs, improved market share of ACTs and reduced the use of older antimalarial drugs among febrile children under five years of age. The research evaluates drug delivery but does not assess whether the patients had confirmed (parasite-diagnosed) malaria. None of the included studies assessed patient outcomes; it is therefore not known whether the effects seen in the studies would translate to an impact on health.

Opiyo N ，Yamey G ，Garner P 《Cochrane Database of Systematic Reviews》

Integrated management of childhood illness (IMCI) strategy for children under five.

More than 7.5 million children younger than age five living in low- and middle-income countries die every year. The World Health Organization (WHO) developed the integrated management of childhood illness (IMCI) strategy to reduce mortality and morbidity and to improve quality of care by improving the delivery of a variety of curative and preventive medical and behavioral interventions at health facilities, at home, and in the community. To evaluate the effects of programs that implement the IMCI strategy in terms of death, nutritional status, quality of care, coverage with IMCI deliverables, and satisfaction of beneficiaries. We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2015, Issue 3), including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register; MEDLINE; EMBASE, Ovid; the Cumulative Index to Nursing and Allied Health Literature (CINAHL), EbscoHost; the Latin American Caribbean Health Sciences Literature (LILACS), Virtual Health Library (VHL); the WHO Library & Information Networks for Knowledge Database (WHOLIS); the Science Citation Index and Social Sciences Citation Index, Institute for Scientific Information (ISI) Web of Science; Population Information Online (POPLINE); the WHO International Clinical Trials Registry Platform (WHO ICTRP); and the Global Health, Ovid and Health Management, ProQuest database. We performed searches until 30 June 2015 and supplemented these by searching revised bibliographies and by contacting experts to identify ongoing and unpublished studies. We sought to include randomised controlled trials (RCTs) and controlled before-after (CBA) studies with at least two intervention and two control sites evaluating the generic IMCI strategy or its adaptation in children younger than age five, and including at minimum efforts to improve health care worker skills for case management. We excluded studies in which IMCI was accompanied by other interventions including conditional cash transfers, food supplementation, and employment. The comparison group received usual health services without provision of IMCI. Two review authors independently screened searches, selected trials, and extracted, analysed and tabulated data. We used inverse variance for cluster trials and an intracluster co-efficient of 0.01 when adjustment had not been made in the primary study. We used the GRADE (Grades of Recommendation, Assessment, Development and Evaluation Working Group) approach to assess the certainty of evidence. Two cluster-randomised trials (India and Bangladesh) and two controlled before-after studies (Tanzania and India) met our inclusion criteria. Strategies included training of health care staff, management strengthening of health care systems (all four studies), and home visiting (two studies). The two studies from India included care packages targeting the neonatal period.One trial in Bangladesh estimated that child mortality may be 13% lower with IMCI, but the confidence interval (CI) included no effect (risk ratio (RR) 0.87, 95% CI 0.68 to 1.10; 5090 participants; low-certainty evidence). One CBA study in Tanzania gave almost identical estimates (RR 0.87, 95% CI 0.72 to 1.05; 1932 participants).One trial in India examined infant and neonatal mortality by implementing the integrated management of neonatal and childhood illness (IMNCI) strategy including post-natal home visits. Neonatal and infant mortality may be lower in the IMNCI group compared with the control group (infant mortality hazard ratio (HR) 0.85, 95% CI 0.77 to 0.94; neonatal mortality HR 0.91, 95% CI 0.80 to 1.03; one trial, 60,480 participants; low-certainty evidence).We estimated the effect of IMCI on any mortality measured by combining infant and child mortality in the one IMCI and the one IMNCI trial. Mortality may be reduced by IMCI (RR 0.85, 95% CI 0.78 to 0.93; two trials, 65,570 participants; low-certainty evidence).Two trials (India, Bangladesh) evaluated nutritional status and noted that there may be little or no effect on stunting (RR 0.94, 95% CI 0.84 to 1.06; 5242 participants, two trials; low-certainty evidence) and there is probably little or no effect on wasting (RR 1.04, 95% CI 0.87 to 1.25; two trials, 4288 participants; moderate-certainty evidence).The Tanzania CBA study showed similar results.Investigators measured quality of care by observing prescribing for common illnesses at health facilities (727 observations, two studies; very low-certainty evidence) and by observing prescribing by lay health care workers (1051 observations, three studies; very low-certainty evidence). We could not confirm a consistent effect on prescribing at health facilities or by lay health care workers, as certainty of the evidence was very low.For coverage of IMCI deliverables, we examined vaccine and vitamin A coverage, appropriate care seeking, and exclusive breast feeding. Two trials (India, Bangladesh) estimated vaccine coverage for measles and reported that there is probably little or no effect on measles vaccine coverage (RR 0.92, 95% CI 0.80 to 1.05; two trials, 4895 participants; moderate-certainty evidence), with similar effects seen in the Tanzania CBA study. Two studies measured the third dose of diphtheria, pertussis, and tetanus vaccine; and two measured vitamin A coverage, all providing little or no evidence of increased coverage with IMCI.Four studies (2 from India, and 1 each from Tanzania and Bangladesh) reported appropriate care seeking and derived information from careful questioning of mothers about recent illness. Some studies on effects of IMCI may report better care seeking behavior, but others do not report this.All four studies recorded maternal responses on exclusive breast feeding. They provided mixed results and very low-certainty evidence. Therefore, we do not know whether IMCI impacts exclusive breast feeding.No studies reported on the satisfaction of mothers and service users. The mix of interventions examined in research studies evaluating the IMCI strategy varies, and some studies include specific inputs to improve neonatal health. Most studies were conducted in South Asia. Implementing the integrated management of childhood illness strategy may reduce child mortality, and packages that include interventions for the neonatal period may reduce infant mortality. IMCI may have little or no effect on nutritional status and probably has little or no effect on vaccine coverage. Maternal care seeking behavior may be more appropriate with IMCI, but study results have been mixed, providing evidence of very low certainty about whether IMCI has effects on adherence to exclusive breast feeding.

Gera T ，Shah D ，Garner P ，Richardson M ，Sachdev HS ... -  《Cochrane Database of Systematic Reviews》