Innovative tools and OpenHDS for health and demographic surveillance on Rusinga Island, Kenya

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass.Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990'sThe paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population.The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.

Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review

Background

A population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system.

Objective

This systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods.

Methods

We conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening.

Results

Our search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems.

Conclusions

Although evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction.

International Registered Report Identifier (IRRID)

RR2-10.2196/10678

Prevalence and risk factors associated with malnutrition among adolescents in rural Tanzania

OBJECTIVE

To determine the prevalence and risk factors associated with malnutrition among adolescents in a rural Tanzanian community.

METHODS

Cross-sectional survey of 1226 randomly selected adolescents from the Dodoma Health and Demographic Surveillance System (HDSS) in the Chamwino district in the Dodoma region. Anthropometric measurements for weight and height were collected. Height-for-age-z-scores (HAZs) and body mass index (BMI)-for-age-z-scores (BAZs) were computed. Descriptive estimates were documented in graphs and tables, and weighted linear regression models were used to examine predictors of malnutrition.

RESULTS

Stunting prevalence was 18%, and thinness prevalence was 14%. Overweight and obesity affected 5.23% of participants. Girls had higher HAZs (β: 0.46, 95% CI 0.33, 0.59, P < 0.0001) and BAZs (β: 0.20, 95% CI 0.05, 0.35, P = 0.0098) than boys. Age was inversely associated with HAZs (β: -0.13, 95% CI -0.17, -0.08, P < 0.0001) and BAZs (β: -0.05, 95% CI -0.10, -0.004, P = 0.0327). Wealth score (β: 0.10, 95% CI 0.04, 0.16, P = 0.0009) and dietary diversity score (β: 0.04, 95% CI 0.01, 0.07, P = 0.0080) were positively associated with HAZs and BAZs. Out-of-school adolescents had higher HAZs (β: -0.49, 95% CI -0.75, -0.23, P = 0.0003) and BAZs (β: -0.68, 95% CI -0.99, -0.37, P < 0.0001) than adolescents who attended school.

CONCLUSION

There are substantial variations of HAZs and BAZs across gender, age, education and wealth, with an emerging burden of overweight and obesity among adolescents in this rural population. Interventions are urgently required to curb both ends of the malnutrition spectrum.

Reducing contamination risk in cluster-randomized infectious disease-intervention trials

Background

Infectious disease interventions are increasingly tested using cluster-randomized trials (CRTs). These trial settings tend to involve a set of sampling units, such as villages, whose geographic arrangement may present a contamination risk in treatment exposure. The most widely used approach for reducing contamination in these settings is the so-called fried-egg design, which excludes the outer portion of all available clusters from the primary trial analysis. However, the fried-egg design ignores potential intra-cluster spatial heterogeneity and makes the outcome measure inherently less precise. Whereas the fried-egg design may be appropriate in specific settings, alternative methods to optimize the design of CRTs in other settings are lacking.

Methods

We present a novel approach for CRT design that either fully includes or fully excludes available clusters in a defined study region, recognizing the potential for intra-cluster spatial heterogeneity. The approach includes an algorithm that allows investigators to identify the maximum number of clusters that could be included for a defined study region and maintain randomness in both the selection of included clusters and the allocation of clusters to either the treatment group or control group. The approach was applied to the design of a CRT testing the effectiveness of malaria vector-control interventions in southern Malawi.

Conclusions

Those planning CRTs to evaluate interventions should consider the approach presented here during trial design. The approach provides a novel framework for reducing the risk of contamination among the CRT randomization units in settings where investigators determine the reduction of contamination risk as a high priority and where intra-cluster spatial heterogeneity is likely. By maintaining randomness in the allocation of clusters to either the treatment group or control group, the approach also permits a randomization-valid test of the primary trial hypothesis.

Open data and public health

This article provides an overview of the intersection of open data and public health by first defining open government data, public health data, and other key concepts and relevant terminologies. There are differing perceptions on the urgency and importance of the openness of public health data. It has been established that disease outbreaks such as happened during the Ebola and Zika virus epidemics are indicative of the need for countries to develop a framework that will provide guidance for the management of public health data. Such a framework should ensure that data collected during public health emergencies are accessible to the appropriate authorities and in a form that can help with timely decision-making during such public health crises. In this article, we highlight available open data policies across many countries, including in the Americas. Our analysis shows that there are currently no articulated policy guidelines for the collection and management of public health data across many countries, especially in Latin America. We propose that any national data governance strategy must address potential benefits, possible risks, examples of data that could be shared, and the attributes of such data. Finally, we stress that the key concern in the Americas should be the development of regional frameworks for open data in public health that can be adopted or adapted by each country through appropriate national or subnational policies and strategies.

Assessment of the effect of larval source management and house improvement on malaria transmission when added to standard malaria control strategies in southern Malawi: study protocol for a cluster-randomised controlled trial

BACKGROUND

Due to outdoor and residual transmission and insecticide resistance, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) will be insufficient as stand-alone malaria vector control interventions in many settings as programmes shift toward malaria elimination. Combining additional vector control interventions as part of an integrated strategy would potentially overcome these challenges. Larval source management (LSM) and structural house improvements (HI) are appealing as additional components of an integrated vector management plan because of their long histories of use, evidence on effectiveness in appropriate settings, and unique modes of action compared to LLINs and IRS. Implementation of LSM and HI through a community-based approach could provide a path for rolling-out these interventions sustainably and on a large scale.

METHODS/DESIGN

We will implement community-based LSM and HI, as additional interventions to the current national malaria control strategies, using a randomised block, 2 × 2 factorial, cluster-randomised design in rural, southern Malawi. These interventions will be continued for two years. The trial catchment area covers about 25,000 people living in 65 villages. Community participation is encouraged by training community volunteers as health animators, and supporting the organisation of village-level committees in collaboration with The Hunger Project, a non-governmental organisation. Household-level cross-sectional surveys, including parasitological and entomological sampling, will be conducted on a rolling, 2-monthly schedule to measure outcomes over two years (2016 to 2018). Coverage of LSM and HI will also be assessed throughout the trial area.

DISCUSSION

Combining LSM and/or HI together with the interventions currently implemented by the Malawi National Malaria Control Programme is anticipated to reduce malaria transmission below the level reached by current interventions alone. Implementation of LSM and HI through a community-based approach provides an opportunity for optimum adaptation to the local ecological and social setting, and enhances the potential for sustainability.

TRIAL REGISTRATION

Registered with The Pan African Clinical Trials Registry on 3 March 2016, trial number PACTR201604001501493.

Assessing the population coverage of a health demographic surveillance system using satellite imagery and crowd-sourcing

Remotely sensed data can serve as an independent source of information about the location of residential structures in areas under demographic and health surveillance. We report on results obtained combining satellite imagery, imported from Bing, with location data routinely collected using the built-in GPS sensors of tablet computers, to assess completeness of population coverage in a Health and Demographic Surveillance System in Malawi. The Majete Malaria Project Health and Demographic Surveillance System, in Malawi, started in 2014 to support a project with the aim of studying the reduction of malaria using an integrated control approach by rolling out insecticide treated nets and improved case management supplemented with house improvement and larval source management. In order to support the monitoring of the trial a Health and Demographic Surveillance System was established in the area that surrounds the Majete Wildlife Reserve (1600 km2), using the OpenHDS data system. We compared house locations obtained using GPS recordings on mobile devices during the demographic surveillance census round with those acquired from satellite imagery. Volunteers were recruited through the crowdcrafting.org platform to identify building structures on the images, which enabled the compilation of a database with coordinates of potential residences. For every building identified on these satellite images by the volunteers (11,046 buildings identified of which 3424 (ca. 30%) were part of the censused area), we calculated the distance to the nearest house enumerated on the ground by fieldworkers during the census round of the HDSS. A random sample of buildings (85 structures) identified on satellite images without a nearby location enrolled in the census were visited by a fieldworker to determine how many were missed during the baseline census survey, if any were missed. The findings from this ground-truthing effort suggest that a high population coverage was achieved in the census survey, however the crowd-sourcing did not locate many of the inhabited structures (52.3% of the 6543 recorded during the census round). We conclude that using auxiliary data can play a useful role in quality assurance in population based health surveillance, but improved algorithms would be needed if crowd-sourced house locations are to be used as the basis of population databases.

The effect of mass mosquito trapping on malaria transmission and disease burden (SolarMal): a stepped-wedge cluster-randomised trial

BACKGROUND

Odour baits can attract host-seeking Anopheles mosquitoes indoors and outdoors. We assessed the effects of mass deployment of odour-baited traps on malaria transmission and disease burden.

METHODS

We installed solar-powered odour-baited mosquito trapping systems (SMoTS) to households on Rusinga Island, Lake Victoria, western Kenya (mean population 24 879), in a stepped-wedge cluster-randomised trial. All residents in the completed health and demographic surveillance system were eligible to participate. We used the travelling salesman algorithm to assign all households to a cluster (50 or 51 geographically contiguous households); nine contiguous clusters formed a metacluster. Initially, no cluster had SMoTS (non-intervened). During the course of the intervention roll-out SMoTS were gradually installed cluster by cluster until all clusters had SMoTS installed (intervened). We generated 27 cluster randomisations, with the cluster as unit of randomisation, to establish the order to install the traps in the clusters until all had a SMoTS installed. Field workers and participants were not masked to group allocation. The primary outcome of clinical malaria was monitored through repeated household visits covering the entire population, once before roll-out (baseline) and five times throughout the 2-year roll-out. We measured clinical malaria as fever plus a positive result with a rapid diagnostic test. The SolarMal project was registered on the Dutch Trial Register (NTR 3496).

FINDINGS

We enrolled 34 041 participants between April 25, 2012, and March 23, 2015, to 81 clusters and nine metaclusters. 4358 households were provided with SMoTS during roll-out between June 3, 2013, and May 16, 2015. 23 clinical malaria episodes were recorded in intervened clusters and 33 episodes in non-intervened clusters (adjusted effectiveness 40·8% [95% CI -172·8 to 87·1], p=0·5) during the roll-out. Malaria prevalence measured by rapid diagnostic test was 29·8% (95% CI 20·9-38·0) lower in SMoTS clusters (prevalence 23·7%; 1552 of 6550 people) than in non-intervened clusters (prevalence 34·5%; 2002 of 5795 people).

INTERPRETATION

The unexpectedly low clinical incidence of malaria during roll-out led to an imprecise estimate of effectiveness from the clinical incidence data. The substantial effect on malaria prevalence is explained by reduction in densities of Anopheles funestus. Odour-baited traps might be an effective malaria intervention.

FUNDING

COmON Foundation.

Mass mosquito trapping for malaria control in western Kenya: study protocol for a stepped wedge cluster-randomised trial

Background

Increasing levels of insecticide resistance as well as outdoor, residual transmission of malaria threaten the efficacy of existing vector control tools used against malaria mosquitoes. The development of odour-baited mosquito traps has led to the possibility of controlling malaria through mass trapping of malaria vectors. Through daily removal trapping against a background of continued bed net use it is anticipated that vector populations could be suppressed to a level where continued transmission of malaria will no longer be possible.

Methods/design

A stepped wedge cluster-randomised trial design was used for the implementation of mass mosquito trapping on Rusinga Island, western Kenya (the SolarMal project). Over the course of 2 years (2013–2015) all households on the island were provided with a solar-powered mosquito trapping system. A continuous health and demographic surveillance system combined with parasitological surveys three times a year, successive rounds of mosquito monitoring and regular sociological studies allowed measurement of intervention outcomes before, during and at completion of the rollout of traps. Data collection continued after achieving mass coverage with traps in order to estimate the longer term effectiveness of this novel intervention. Solar energy was exploited to provide electric light and mobile phone charging for each household, and the impacts of these immediate tangible benefits upon acceptability of and adherence to the use of the intervention are being measured.

Discussion

This study will be the first to evaluate whether the principle of solar-powered mass mosquito trapping could be an effective tool for elimination of malaria. If proven to be effective, this novel approach to malaria control would be a valuable addition to the existing strategies of long-lasting insecticide-treated nets and case management. Sociological studies provide a knowledge base for understanding the usage of this novel tool.

Trial registration

Trialregister.nl: NTR3496 – SolarMal. Registered on 20 June 2012.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-016-1469-z) contains supplementary material, which is available to authorized users.