The effect of community-driven larval source management and house improvement on malaria transmission when added to the standard malaria control strategies in Malawi: a cluster-randomized controlled trial.

BACKGROUND: Current standard interventions are not universally sufficient for malaria elimination. The effects of community-based house improvement (HI) and larval source management (LSM) as supplementary interventions to the Malawi National Malaria Control Programme (NMCP) interventions were assessed in the context of an intensive community engagement programme. METHODS: The study was a two-by-two factorial, cluster-randomized controlled trial in Malawi. Village clusters were randomly assigned to four arms: a control arm; HI; LSM; and HI + LSM. Malawi NMCP interventions and community engagement were used in all arms. Household-level, cross-sectional surveys were conducted on a rolling, 2-monthly basis to measure parasitological and entomological outcomes over 3 years, beginning with one baseline year. The primary outcome was the entomological inoculation rate (EIR). Secondary outcomes included mosquito density, Plasmodium falciparum prevalence, and haemoglobin levels. All outcomes were assessed based on intention to treat, and comparisons between trial arms were conducted at both cluster and household level. RESULTS: Eighteen clusters derived from 53 villages with 4558 households and 20,013 people were randomly assigned to the four trial arms. The mean nightly EIR fell from 0.010 infectious bites per person (95% CI 0.006-0.015) in the baseline year to 0.001 (0.000, 0.003) in the last year of the trial. Over the full trial period, the EIR did not differ between the four trial arms (p = 0.33). Similar results were observed for the other outcomes: mosquito density and P. falciparum prevalence decreased over 3 years of sampling, while haemoglobin levels increased; and there were minimal differences between the trial arms during the trial period. CONCLUSIONS: In the context of high insecticide-treated bed net use, neither community-based HI, LSM, nor HI + LSM contributed to further reductions in malaria transmission or prevalence beyond the reductions observed over two years across all four trial arms. This was the first trial, as far as the authors are aware, to test the potential complementary impact of LSM and/or HI beyond levels achieved by standard interventions. The unexpectedly low EIR values following intervention implementation indicated a promising reduction in malaria transmission for the area, but also limited the usefulness of this outcome for measuring differences in malaria transmission among the trial arms. Trial registration PACTR, PACTR201604001501493, Registered 3 March 2016, https://pactr.samrc.ac.za/ .

Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy.

Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale.

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.

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.

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.

Profile: The Rusinga Health and Demographic Surveillance System, Western Kenya.

The health and demographic surveillance system on Rusinga Island, Western Kenya, was initiated in 2012 to facilitate a malaria intervention trial: the SolarMal project. The project aims to eliminate malaria from Rusinga Island using the nationwide adopted strategy for malaria control (insecticide-treated bed nets and case management) augmented with mass trapping of anopheline mosquitoes. The main purpose of the health and demographic surveillance is to measure the effectiveness of the trial on clinical malaria incidence, and to monitor demographic, environmental and malaria-related data variables. At the end of 2014, the 44 km(2) island had a population of approximately 25 000 individuals living in 8746 residential structures. Three times per year, all individuals are followed up and surveyed for clinical malaria. Following each round of surveillance, a randomly selected cross-section of the population is subject to a rapid diagnostic test to measure malaria. Additionally, extensive monitoring of malaria vectors is performed. Data collection and management are conducted using the OpenHDS platform, with tablet computers and applications with advanced software connected to a centralized database. Besides the general demographic information, other health-related data are collected which can be used to facilitate a range of other studies within and outside the current project. Access to the core dataset can be obtained on request from the authors.

Spatially variable risk factors for malaria in a geographically heterogeneous landscape, western Kenya: an explorative study.

BACKGROUND: Large reductions in malaria transmission and mortality have been achieved over the last decade, and this has mainly been attributed to the scale-up of long-lasting insecticidal bed nets and indoor residual spraying with insecticides. Despite these gains considerable residual, spatially heterogeneous, transmission remains. To reduce transmission in these foci, researchers need to consider the local demographical, environmental and social context, and design an appropriate set of interventions. Exploring spatially variable risk factors for malaria can give insight into which human and environmental characteristics play important roles in sustaining malaria transmission. METHODS: On Rusinga Island, western Kenya, malaria infection was tested by rapid diagnostic tests during two cross-sectional surveys conducted 3 months apart in 3632 individuals from 790 households. For all households demographic data were collected by means of questionnaires. Environmental variables were derived using Quickbird satellite images. Analyses were performed on 81 project clusters constructed by a traveling salesman algorithm, each containing 50-51 households. A standard linear regression model was fitted containing multiple variables to determine how much of the spatial variation in malaria prevalence could be explained by the demographic and environmental data. Subsequently, a geographically-weighted regression (GWR) was performed assuming non-stationarity of risk factors. Special attention was taken to investigate the effect of residual spatial autocorrelation and local multicollinearity. RESULTS: Combining the data from both surveys, overall malaria prevalence was 24%. Scan statistics revealed two clusters which had significantly elevated numbers of malaria cases compared to the background prevalence across the rest of the study area. A multivariable linear model including environmental and household factors revealed that higher socioeconomic status, outdoor occupation and population density were associated with increased malaria risk. The local GWR model improved the model fit considerably and the relationship of malaria with risk factors was found to vary spatially over the island; in different areas of the island socio-economic status, outdoor occupation and population density were found to be positively or negatively associated with malaria prevalence. DISCUSSION: Identification of risk factors for malaria that vary geographically can provide insight into the local epidemiology of malaria. Examining spatially variable relationships can be a helpful tool in exploring which set of targeted interventions could locally be implemented. Supplementary malaria control may be directed at areas, which are identified as at risk. For instance, areas with many people that work outdoors at night may need more focus in terms of vector control. TRIAL REGISTRATION: Trialregister.nl NTR3496-SolarMal, registered on 20 June 2012.

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

BACKGROUND: Health in low and middle income countries is on one hand characterized by a high burden associated with preventable communicable diseases and on the other hand considered to be under-documented due to improper basic health and demographic record-keeping. health and demographic surveillance systems (HDSSs) have provided researchers, policy makers and governments with data about local population dynamics and health related information. In order for an HDSS to deliver high quality data, effective organization of data collection and management are vital. HDSSs impose a challenging logistical process typically characterized by door to door visits, poor navigational guidance, conducting interviews recorded on paper, error prone data entry, an extensive staff and marginal data quality management possibilities. METHODS: A large trial investigating the effect of odour-baited mosquito traps on malaria vector populations and malaria transmission on Rusinga Island, western Kenya, has deployed an HDSS. By means of computer tablets in combination with Open Data Kit and OpenHDS data collection and management software experiences with time efficiency, cost effectiveness and high data quality are illustrate. Step by step, a complete organization of the data management infrastructure is described, ranging from routine work in the field to the organization of the centralized data server. RESULTS AND DISCUSSION: Adopting innovative technological advancements has enabled the collection of demographic and malaria data quickly and effectively, with minimal margin for errors. Real-time data quality controls integrated within the system can lead to financial savings and a time efficient work flow. CONCLUSION: This novel method of HDSS implementation demonstrates the feasibility of integrating electronic tools in large-scale health interventions.

Modelling the cost-effectiveness of mass screening and treatment for reducing Plasmodium falciparum malaria burden.

BACKGROUND: Past experience and modelling suggest that, in most cases, mass treatment strategies are not likely to succeed in interrupting Plasmodium falciparum malaria transmission. However, this does not preclude their use to reduce disease burden. Mass screening and treatment (MSAT) is preferred to mass drug administration (MDA), as the latter involves massive over-use of drugs. This paper reports simulations of the incremental cost-effectiveness of well-conducted MSAT campaigns as a strategy for P. falciparum malaria disease-burden reduction in settings with varying receptivity (ability of the combined vector population in a setting to transmit disease) and access to case management. METHODS: MSAT incremental cost-effectiveness ratios (ICERs) were estimated in different sub-Saharan African settings using simulation models of the dynamics of malaria and a literature-based MSAT cost estimate. Imported infections were simulated at a rate of two per 1,000 population per annum. These estimates were compared to the ICERs of scaling up case management or insecticide-treated net (ITN) coverage in each baseline health system, in the absence of MSAT. RESULTS: MSAT averted most episodes, and resulted in the lowest ICERs, in settings with a moderate level of disease burden. At a low pre-intervention entomological inoculation rate (EIR) of two infectious bites per adult per annum (IBPAPA) MSAT was never more cost-effective than scaling up ITNs or case management coverage. However, at pre-intervention entomological inoculation rates (EIRs) of 20 and 50 IBPAPA and ITN coverage levels of 40 or 60%, respectively, the ICER of MSAT was similar to that of scaling up ITN coverage further. CONCLUSIONS: In all the transmission settings considered, achieving a minimal level of ITN coverage is a "best buy". At low transmission, MSAT probably is not worth considering. Instead, MSAT may be suitable at medium to high levels of transmission and at moderate ITN coverage. If undertaken as a burden-reducing intervention, MSAT should be continued indefinitely and should complement, not replace, case management and vector control interventions.

Toward an open-access global database for mapping, control, and surveillance of neglected tropical diseases.

BACKGROUND: After many years of general neglect, interest has grown and efforts came under way for the mapping, control, surveillance, and eventual elimination of neglected tropical diseases (NTDs). Disease risk estimates are a key feature to target control interventions, and serve as a benchmark for monitoring and evaluation. What is currently missing is a georeferenced global database for NTDs providing open-access to the available survey data that is constantly updated and can be utilized by researchers and disease control managers to support other relevant stakeholders. We describe the steps taken toward the development of such a database that can be employed for spatial disease risk modeling and control of NTDs. METHODOLOGY: With an emphasis on schistosomiasis in Africa, we systematically searched the literature (peer-reviewed journals and 'grey literature'), contacted Ministries of Health and research institutions in schistosomiasis-endemic countries for location-specific prevalence data and survey details (e.g., study population, year of survey and diagnostic techniques). The data were extracted, georeferenced, and stored in a MySQL database with a web interface allowing free database access and data management. PRINCIPAL FINDINGS: At the beginning of 2011, our database contained more than 12,000 georeferenced schistosomiasis survey locations from 35 African countries available under http://www.gntd.org. Currently, the database is expanded to a global repository, including a host of other NTDs, e.g. soil-transmitted helminthiasis and leishmaniasis. CONCLUSIONS: An open-access, spatially explicit NTD database offers unique opportunities for disease risk modeling, targeting control interventions, disease monitoring, and surveillance. Moreover, it allows for detailed geostatistical analyses of disease distribution in space and time. With an initial focus on schistosomiasis in Africa, we demonstrate the proof-of-concept that the establishment and running of a global NTD database is feasible and should be expanded without delay.