Profiling Nonrecipients of Mass Drug Administration for Schistosomiasis and Hookworm Infections: A Comprehensive Analysis of Praziquantel and Albendazole Coverage in Community-Directed Treatment in Uganda.

BACKGROUND: Repeated mass drug administration (MDA) with preventive chemotherapies is the mainstay of morbidity control for schistosomiasis and soil-transmitted helminths, yet the World Health Organization recently reported that less than one-third of individuals who required preventive chemotherapies received treatment. METHODS: Coverage of community-directed treatment with praziquantel (PZQ) and albendazole (ALB) was analyzed in 17 villages of Mayuge District, Uganda. National drug registers, household questionnaires, and parasitological surveys were collected to track 935 individuals before and after MDA. Multilevel logistic regressions, including household and village effects, were specified with a comprehensive set of socioeconomic and parasitological variables. The factors predicting who did not receive PZQ and ALB from community medicine distributors were identified. RESULTS: Drug receipt was correlated among members within a household, and nonrecipients of PZQ or ALB were profiled by household-level socioeconomic factors. Individuals were less likely to receive either PZQ or ALB if they had a Muslim household head or low home quality, belonged to the minority tribe, or had settled for more years in their village. Untreated individuals were also more likely to belong to households that did not purify drinking water, had no home latrine, and had no members who were part of the village government. CONCLUSIONS: The findings demonstrate how to locate and target individuals who are not treated in MDA. Infection risk factors were not informative. In particular, age, gender, and occupation were unable to identify non-recipients, although World Health Organization guidelines rely on these factors. Individuals of low socioeconomic status, minority religions, and minority tribes can be targeted to expand MDA coverage.

Diffusion of treatment in social networks and mass drug administration.

Information, behaviors, and technologies spread when people interact. Understanding these interactions is critical for achieving the greatest diffusion of public interventions. Yet, little is known about the performance of starting points (seed nodes) for diffusion. We track routine mass drug administration-the large-scale distribution of deworming drugs-in Uganda. We observe friendship networks, socioeconomic factors, and treatment delivery outcomes for 16,357 individuals in 3491 households of 17 rural villages. Each village has two community medicine distributors (CMDs), who are the seed nodes and responsible for administering treatments. Here, we show that CMDs with tightly knit (clustered) friendship connections achieve the greatest reach and speed of treatment coverage. Importantly, we demonstrate that clustering predicts diffusion through social networks when spreading relies on contact with seed nodes while centrality is unrelated to diffusion. Clustering should be considered when selecting seed nodes for large-scale treatment campaigns.

Community-directed mass drug administration is undermined by status seeking in friendship networks and inadequate trust in health advice networks.

Over 1.9 billion individuals require preventive chemotherapy through mass drug administration (MDA). Community-directed MDA relies on volunteer community medicine distributors (CMDs) and their achievement of high coverage and compliance. Yet, it is unknown if village social networks influence effective MDA implementation by CMDs. In Mayuge District, Uganda, census-style surveys were conducted for 16,357 individuals from 3,491 households in 17 villages. Praziquantel, albendazole, and ivermectin were administered for one month in community-directed MDA to treat Schistosoma mansoni, hookworm, and lymphatic filariasis. Self-reported treatment outcomes, socioeconomic characteristics, friendship networks, and health advice networks were collected. We investigated systematically missed coverage and noncompliance. Coverage was defined as an eligible person being offered at least one drug by CMDs; compliance included ingesting at least one of the offered drugs. These outcomes were analyzed as a two-stage process using a Heckman selection model. To further assess if MDA through CMDs was working as intended, we examined the probability of accurate drug administration of 1) praziquantel, 2) both albendazole and ivermectin, and 3) all drugs. This analysis was conducted using bivariate Probit regression. Four indicators from each social network were examined: degree, betweenness centrality, closeness centrality, and the presence of a direct connection to CMDs. All models accounted for nested household and village standard errors. CMDs were more likely to offer medicines, and to accurately administer the drugs as trained by the national control programme, to individuals with high friendship degree (many connections) and high friendship closeness centrality (households that were only a short number of steps away from all other households in the network). Though high (88.59%), additional compliance was associated with directly trusting CMDs for health advice. Effective treatment provision requires addressing CMD biases towards influential, well-embedded individuals in friendship networks and utilizing health advice networks to increase village trust in CMDs.

Influence of Schistosoma mansoni and Hookworm Infection Intensities on Anaemia in Ugandan Villages.

BACKGROUND: The association of anaemia with intestinal schistosomiasis and hookworm infections are poorly explored in populations that are not limited to children or pregnant women. METHODS: We sampled 1,832 individuals aged 5-90 years from 30 communities in Mayuge District, Uganda. Demographic, village, and parasitological data were collected. Infection risk factors were compared in ordinal logistic regressions. Anaemia and infection intensities were analyzed in multilevel models, and population attributable fractions were estimated. FINDINGS: Household and village-level predictors of Schistosoma mansoni and hookworm were opposite in direction or significant for single infections. S. mansoni was found primarily in children, whereas hookworm was prevalent amongst the elderly. Anaemia was more prevalent in individuals with S. mansoni and increased by 2.86 fold (p-value<0.001) with heavy S. mansoni infection intensity. Individuals with heavy hookworm were 1.65 times (p-value = 0.008) more likely to have anaemia than uninfected participants. Amongst individuals with heavy S. mansoni infection intensity, 32.0% (p-value<0.001) of anaemia could be attributed to S. mansoni. For people with heavy hookworm infections, 23.7% (p-value = 0.002) of anaemia could be attributed to hookworm. A greater fraction of anaemia (24.9%, p-value = 0.002) was attributable to heavy hookworm infections in adults (excluding pregnant women) as opposed to heavy hookworm infections in school-aged children and pregnant women (20.2%, p-value = 0.001). CONCLUSION: Community-based surveys captured anaemia in children and adults affected by S. mansoni and hookworm infections. For areas endemic with schistosomiasis or hookworm infections, WHO guidelines should include adults for treatment in helminth control programmes.

Social network analysis predicts health behaviours and self-reported health in African villages.

The provision of healthcare in rural African communities is a highly complex and largely unsolved problem. Two main difficulties are the identification of individuals that are most likely affected by disease and the prediction of responses to health interventions. Social networks have been shown to capture health outcomes in a variety of contexts. Yet, it is an open question as to what extent social network analysis can identify and distinguish among households that are most likely to report poor health and those most likely to respond to positive behavioural influences. We use data from seven highly remote, post-conflict villages in Liberia and compare two prominent network measures: in-degree and betweenness. We define in-degree as the frequency in which members from one household are named by another household as a friends. Betweenness is defined as the proportion of shortest friendship paths between any two households in a network that traverses a particular household. We find that in-degree explains the number of ill family members, whereas betweenness explains engagement in preventative health. In-degree and betweenness independently explained self-reported health and behaviour, respectively. Further, we find that betweenness predicts susceptibility to, instead of influence over, good health behaviours. The results suggest that targeting households based on network measures rather than health status may be effective for promoting the uptake of health interventions in rural poor villages.

Exploring network theory for mass drug administration.

Network theory is a well-established discipline that uses mathematical graphs to describe biological, physical, and social systems. The topologies across empirical networks display strikingly similar organizational properties. In particular, the characteristics of these networks allow computational analysis to contribute data unattainable from examining individual components in isolation. However, the interdisciplinary and quantitative nature of network analysis has yet to be exploited by public health initiatives to distribute preventive chemotherapies. One notable application is the 2012 World Health Organization (WHO) Roadmap for Neglected Tropical Diseases (NTDs) where there is a need to upscale distribution capacity and to target systematic noncompliers. An understanding of local networks for analysing the distributional properties of community-directed treatment may facilitate sustainable expansion of mass drug-administration (MDA) programs.