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Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials.

ABSTRACT: BACKGROUND:Sample size calculations for cluster randomized trials are a recognized methodological challenge for malaria research in pre-elimination settings. Positively correlated responses from the participants in the same cluster are a key feature in the estimated sample size required for a cluster randomized trial. The degree of correlation is measured by the intracluster correlation coefficient (ICC) where a higher coefficient suggests a closer correlation hence less heterogeneity within clusters but more heterogeneity between clusters. METHODS:Data on uPCR-detected Plasmodium falciparum and Plasmodium vivax infections from a recent cluster randomized trial which aimed at interrupting malaria transmission through mass drug administrations were used to calculate the ICCs for prevalence and incidence of Plasmodium infections. The trial was conducted in four countries in the Greater Mekong Subregion, Laos, Myanmar, Vietnam and Cambodia. Exact and simulation approaches were used to estimate ICC values for both the prevalence and the incidence of parasitaemia. In addition, the latent variable approach to estimate ICCs for the prevalence was utilized. RESULTS:The ICCs for prevalence ranged between 0.001 and 0.082 for all countries. The ICC from the combined 16 villages in the Greater Mekong Subregion were 0.26 and 0.21 for P. falciparum and P. vivax respectively. The ICCs for incidence of parasitaemia ranged between 0.002 and 0.075 for Myanmar, Cambodia and Vietnam. There were very high ICCs for incidence in the range of 0.701 to 0.806 in Laos during follow-up. CONCLUSION:ICC estimates can help researchers when designing malaria cluster randomized trials. A high variability in ICCs and hence sample size requirements between study sites was observed. Realistic sample size estimates for cluster randomized malaria trials in the Greater Mekong Subregion have to assume high between cluster heterogeneity and ICCs. This work focused on uPCR-detected infections; there remains a need to develop more ICC references for trials designed around prevalence and incidence of clinical outcomes. Adequately powered trials are critical to estimate the benefit of interventions to malaria in a reliable and reproducible fashion. TRIAL REGISTRATION:ClinicalTrials.govNCT01872702. Registered 7 June 2013. Retrospectively registered. https://clinicaltrials.gov/ct2/show/NCT01872702.

SUBMITTER: Peerawaranun P

PROVIDER: S-EPMC6921387 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials.

Peerawaranun Pimnara P Landier Jordi J Nosten Francois H FH Nguyen Thuy-Nhien TN Hien Tran Tinh TT Tripura Rupam R Peto Thomas J TJ Phommasone Koukeo K Mayxay Mayfong M Day Nicholas P J NPJ Dondorp Arjen A White Nick N von Seidlein Lorenz L Mukaka Mavuto M

Malaria journal 20191218 1

<h4>Background</h4>Sample size calculations for cluster randomized trials are a recognized methodological challenge for malaria research in pre-elimination settings. Positively correlated responses from the participants in the same cluster are a key feature in the estimated sample size required for a cluster randomized trial. The degree of correlation is measured by the intracluster correlation coefficient (ICC) where a higher coefficient suggests a closer correlation hence less heterogeneity wi ...[more]

PMID: 31852499

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Project description:Background/aimsGeneralized estimating equations are commonly used to fit logistic regression models to clustered binary data from cluster randomized trials. A commonly used correlation structure assumes that the intracluster correlation coefficient does not vary by treatment arm or other covariates, but the consequences of this assumption are understudied. We aim to evaluate the effect of allowing variation of the intracluster correlation coefficient by treatment or other covariates on the efficiency of analysis and show how to account for such variation in sample size calculations.MethodsWe develop formulae for the asymptotic variance of the estimated difference in outcome between treatment arms obtained when the true exchangeable correlation structure depends on the treatment arm and the working correlation structure used in the generalized estimating equations analysis is: (i) correctly specified, (ii) independent, or (iii) exchangeable with no dependence on treatment arm. These formulae require a known distribution of cluster sizes; we also develop simplifications for the case when cluster sizes do not vary and approximations that can be used when the first two moments of the cluster size distribution are known. We then extend the results to settings with adjustment for a second binary cluster-level covariate. We provide formulae to calculate the required sample size for cluster randomized trials using these variances.ResultsWe show that the asymptotic variance of the estimated difference in outcome between treatment arms using these three working correlation structures is the same if all clusters have the same size, and this asymptotic variance is approximately the same when intracluster correlation coefficient values are small. We illustrate these results using data from a recent cluster randomized trial for infectious disease prevention in which the clusters are groups of households and modest in size (mean 9.6 individuals), with intracluster correlation coefficient values of 0.078 in the control arm and 0.057 in an intervention arm. In this application, we found a negligible difference between the variances calculated using structures (i) and (iii) and only a small increase (typically <5%) for the independent correlation structure (ii), and hence minimal effect on power or sample size requirements. The impact may be larger in other applications if there is greater variation in the ICC between treatment arms or with an additional covariate.ConclusionThe common approach of fitting generalized estimating equations with an exchangeable working correlation structure with a common intracluster correlation coefficient across arms likely does not substantially reduce the power or efficiency of the analysis in the setting of a large number of small or modest-sized clusters, even if the intracluster correlation coefficient varies by treatment arm. Our formulae, however, allow formal evaluation of this and may identify situations in which variation in intracluster correlation coefficient by treatment arm or another binary covariate may have a more substantial impact on power and hence sample size requirements.

Project description:BackgroundPrivate sector malaria programmes contribute to government-led malaria elimination strategies in Cambodia, Lao PDR, and Myanmar by increasing access to quality malaria services and surveillance data. However, reporting from private sector providers remains suboptimal in many settings. To support surveillance strengthening for elimination, a key programme strategy is to introduce electronic surveillance tools and systems to integrate private sector data with national systems, and enhance the use of data for decision-making. During 2013-2017, an electronic surveillance system based on open source software, District Health Information System 2 (DHIS2), was implemented as part of a private sector malaria case management and surveillance programme. The electronic surveillance system covered 16,000 private providers in Myanmar (electronic reporting conducted by 200 field officers with tablets), 710 in Cambodia (585 providers reporting through mobile app), and 432 in Laos (250 providers reporting through mobile app).MethodsThe purpose of the study was to document the costs of introducing electronic surveillance systems and mobile reporting solutions in Cambodia, Lao PDR, and Myanmar, comparing the cost in different operational settings, the cost of introduction and maintenance over time, and assessing the affordability and financial sustainability of electronic surveillance. The data collection methods included extracting data from PSI's financial and operational records, collecting data on prices and quantities of resources used, and interviewing key informants in each setting. The costing study used an ingredients-based approach and estimated both financial and economic costs.ResultsAnnual economic costs of electronic surveillance systems were $152,805 in Laos, $263,224 in Cambodia, and $1,310,912 in Myanmar. The annual economic cost per private provider surveilled was $82 in Myanmar, $371 in Cambodia, and $354 in Laos. Cost drivers varied depending on operational settings and number of private sector outlets covered in each country; whether purchased or personal mobile devices were used; and whether electronic (mobile) reporting was introduced at provider level or among field officers who support multiple providers for case reporting.ConclusionThe study found that electronic surveillance comprises about 0.5-1.5% of national malaria strategic plan cost and 7-21% of surveillance budgets and deemed to be affordable and financially sustainable.

Project description:BackgroundMalaria reactive case detection is the testing and, if positive, treatment of close contacts of index cases. It is included in national malaria control programmes of countries in the Greater Mekong Subregion to accelerate malaria elimination. Yet the value of reactive case detection in the control and elimination of malaria remains controversial because of the low yield, limited evidence for impact, and high demands on resources.MethodsData from the epidemiological assessments of large mass drug administration (MDA) studies in Myanmar, Vietnam, Cambodia and Laos were analysed to explore malaria infection clustering in households. The proportion of malaria positive cases among contacts screened in a hypothetical reactive case detection programme was then determined. The parasite density thresholds for rapid diagnostic test (RDT) detection was assumed to be > 50/µL (50,000/mL), for dried-blood-spot (DBS) based PCR > 5/µL (5000/mL), and for ultrasensitive PCR (uPCR) with a validated limit of detection at 0.0022/µL (22/mL).ResultsAt baseline, before MDA, 1223 Plasmodium infections were detected by uPCR in 693 households. There was clustering of Plasmodium infections. In 637 households with asymptomatic infections 44% (278/637) had more than one member with Plasmodium infections. In the 132 households with symptomatic infections, 65% (86/132) had more than one member with Plasmodium infections. At baseline 4% of households had more than one Plasmodium falciparum infection, but three months after MDA no household had more than one P. falciparum infected member. Reactive case detection using DBS PCR would have detected ten additional cases in six households, and an RDT screen would have detected five additional cases in three households among the 169 households with at least one RDT positive case. This translates to 19 and 9 additional cases identified per 1000 people screened, respectively. Overall, assuming all febrile RDT positive patients would seek treatment and provoke reactive case detection using RDTs, then 1047 of 1052 (99.5%) Plasmodium infections in these communities would have remained undetected.ConclusionReactive case detection in the Greater Mekong subregion is predicted to have a negligible impact on the malaria burden, but it has substantial costs in terms of human and financial resources.

Project description:BackgroundNational Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures.MethodsSamples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs.ResultsGenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs.ConclusionsGenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community.FundingThe GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases.

Project description:Novel vector control methods that can directly target outdoor malaria transmission are urgently needed in the Greater Mekong Subregion (GMS) to accelerate malaria elimination and artemisinin resistance containment efforts. Ivermectin mass drug administration (MDA) to humans has been shown to effectively kill wild Anopheles and suppress malaria transmission in West Africa. Preliminary laboratory investigations were performed to determine ivermectin susceptibility and sporontocidal effect in GMS Anopheles malaria vectors coupled with pharmacokinetic models of ivermectin at escalating doses.A population-based pharmacokinetic model of ivermectin was developed using pre-existing data from a clinical trial conducted in Thai volunteers at the 200 µg/kg dose. To assess ivermectin susceptibility, various concentrations of ivermectin compound were mixed in human blood meals and blood-fed to Anopheles dirus, Anopheles minimus, Anopheles sawadwongporni, and Anopheles campestris. Mosquito survival was monitored daily for 7 days and a non-linear mixed effects model with probit analyses was used to calculate concentrations of ivermectin that killed 50% (LC50) of mosquitoes for each species. Blood samples were collected from Plasmodium vivax positive patients and offered to mosquitoes with or without ivermectin at the ivermectin LC25 or LC5 for An. dirus and An. minimus.The GMS Anopheles displayed a range of susceptibility to ivermectin with species listed from most to least susceptible being An. minimus (LC50 = 16.3 ng/ml) > An. campestris (LC50 = 26.4 ng/ml) = An. sawadwongporni (LC50 = 26.9 ng/ml) > An. dirus (LC50 = 55.6 ng/ml). Mosquito survivorship results, the pharmacokinetic model, and extensive safety data indicated that ivermectin 400 µg/kg is the ideal minimal dose for MDA in the GMS for malaria parasite transmission control. Ivermectin compound was sporontocidal to P. vivax in both An. dirus and An. minimus at the LC25 and LC5 concentrations.Ivermectin is lethal to dominant GMS Anopheles malaria vectors and inhibits sporogony of P. vivax at safe human relevant concentrations. The data suggest that ivermectin MDA has potential in the GMS as a vector and transmission blocking control tool to aid malaria elimination efforts.

Project description:BackgroundThe malaria elimination plan of the Greater Mekong Subregion (GMS) is jeopardized by the increasing number of Plasmodium vivax infections and emergence of parasite strains with reduced susceptibility to the frontline drug treatment chloroquine/primaquine. This study aimed to determine the evolution of the P. vivax multidrug resistance 1 (Pvmdr1) gene in P. vivax parasites isolated from the China-Myanmar border area during the major phase of elimination.MethodsClinical isolates were collected from 275 P. vivax patients in 2008, 2012-2013 and 2015 in the China-Myanmar border area and from 55 patients in central China. Comparison was made with parasites from three border regions of Thailand.ResultsOverall, genetic diversity of the Pvmdr1 was relatively high in all border regions, and over the seven years in the China-Myanmar border, though slight temporal fluctuation was observed. Single nucleotide polymorphisms previously implicated in reduced chloroquine sensitivity were detected. In particular, M908L approached fixation in the China-Myanmar border area. The Y976F mutation sharply decreased from 18.5% in 2008 to 1.5% in 2012-2013 and disappeared in 2015, whereas F1076L steadily increased from 33.3% in 2008 to 77.8% in 2015. While neutrality tests suggested the action of purifying selection on the pvmdr1 gene, several likelihood-based algorithms detected positive as well as purifying selections operating on specific amino acids including M908L, T958M and F1076L. Fixation and selection of the nonsynonymous mutations are differently distributed across the three border regions and central China. Comparison with the global P. vivax populations clearly indicated clustering of haplotypes according to geographic locations. It is noteworthy that the temperate-zone parasites from central China were completely separated from the parasites from other parts of the GMS.ConclusionsThis study showed that P. vivax populations in the China-Myanmar border has experienced major changes in the Pvmdr1 residues proposed to be associated with chloroquine resistance, suggesting that drug selection may play an important role in the evolution of this gene in the parasite populations.

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Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials.

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Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials.

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