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Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach.

ABSTRACT: Public health researchers and social scientists highlight the promise of network-based strategies to inform and enhance interventions that curb risky adolescent health behaviors. However, we currently lack an understanding of how different variants of network-based interventions shape the distribution of targeted behaviors. The current project considers the effectiveness of five targeting strategies that are designed to have differential impacts on the health of program participants versus non-participants. Using simulations that are empirically-grounded in 28 observed school-based networks from the PROSPER study, we evaluate how these approaches shape long-term alcohol use for intervention participants and non-participants, separately, and consider whether contextual factors moderate their success. Findings suggest that enrolling well-connected adolescents results in the lowest drinking levels for non-participants, while strategies that target groups of friends excel at protecting participants from harmful influences. These trends become increasingly pronounced in contexts characterized by higher levels of peer influence.

SUBMITTER: McMillan C

PROVIDER: S-EPMC8299477 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach.

McMillan Cassie C Schaefer David R DR

Social science & medicine (1982) 20210616

Public health researchers and social scientists highlight the promise of network-based strategies to inform and enhance interventions that curb risky adolescent health behaviors. However, we currently lack an understanding of how different variants of network-based interventions shape the distribution of targeted behaviors. The current project considers the effectiveness of five targeting strategies that are designed to have differential impacts on the health of program participants versus non-p ...[more]

PMID: 34175574

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Project description:BackgroundIndoor residual spraying (IRS) is an effective method to control malaria-transmitting Anopheles mosquitoes and often complements insecticide-treated mosquito nets, the predominant malaria vector control intervention. With insufficient funds to cover every household, malaria control programs must balance the malaria risk to a particular human community against the financial cost of spraying that community. This study creates a framework for modelling the distance to households for targeting IRS implementation, and applies it to potential risk prioritization strategies in four provinces (Luapula, Muchinga, Eastern, and Northern) in Zambia.MethodsOptimal network models were used to assess the travel distance of routes between operations bases and human communities identified through remote sensing. Network travel distances were compared to Euclidean distances, to demonstrate the importance of accounting for road routes. The distance to reaching communities for different risk prioritization strategies were then compared assuming sufficient funds to spray 50% of households, using four underlying malarial risk maps: (a) predicted Plasmodium falciparum parasite rate in 2-10 years olds (PfPR), or (b) predicted probability of the presence of each of three main malaria transmitting anopheline vectors (Anopheles arabiensis, Anopheles funestus, Anopheles gambiae).ResultsThe estimated one-way network route distance to reach communities to deliver IRS ranged from 0.05 to 115.69 km. Euclidean distance over and under-estimated these routes by - 101.21 to 41.79 km per trip, as compared to the network route method. There was little overlap between risk map prioritization strategies, both at a district-by-district scale, and across all four provinces. At both scales, agreement for inclusion or exclusion from IRS across all four prioritization strategies occurred in less than 10% of houses. The distances to reaching prioritized communities were either lower, or not statistically different from non-prioritized communities, at both scales of strategy.ConclusionVariation in distance to targeted communities differed depending on risk prioritization strategy used, and higher risk prioritization did not necessarily translate into greater distances in reaching a human community. These findings from Zambia suggest that areas with higher malaria burden may not necessarily be more remote than areas with lower malaria burden.

Project description:Molecular networks are built up from genetic elements that exhibit feedback interactions. Here, we studied the problem of measuring the similarity of directed networks by proposing a novel alignment-free approach: the network subgraph-based approach. Our approach does not make use of randomized networks to determine modular patterns embedded in a network, and this method differs from the network motif and graphlet methods. Network similarity was quantified by gauging the difference between the subgraph frequency distributions of two networks using Jensen-Shannon entropy. We applied the subgraph approach to study three types of molecular networks, i.e., cancer networks, signal transduction networks, and cellular process networks, which exhibit diverse molecular functions. We compared the performance of our subgraph detection algorithm with other algorithms, and the results were consistent, but other algorithms could not address the issue of subgraphs/motifs embedded within a subgraph/motif. To evaluate the effectiveness of the subgraph-based method, we applied the method along with the Jensen-Shannon entropy to classify six network models, and it achieves a 100% accuracy of classification. The proposed information-theoretic approach allows us to determine the structural similarity of two networks regardless of node identity and network size. We demonstrated the effectiveness of the subgraph approach to cluster molecular networks that exhibit similar regulatory interaction topologies. As an illustration, our method can identify (i) common subgraph-mediated signal transduction and/or cellular processes in AML and pancreatic cancer, and (ii) scaffold proteins in gastric cancer and hepatocellular carcinoma; thus, the results suggested that there are common regulation modules for cancer formation. We also found that the underlying substructures of the molecular networks are dominated by irreducible subgraphs; this feature is valid for the three classes of molecular networks we studied. The subgraph-based approach provides a systematic scenario for analyzing, compare and classifying molecular networks with diverse functionalities.

Dataset Information

Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach.

Publications

Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach.

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