{
  "abstract": "Introduction The China-UK-Tanzania pilot project of 1,7-malaria reactive community-based testing and response (1,7-mRCTR) approach was implemented in Tanzania between 2015 and 2018. This project targeted villages with the highest malaria incidence to conduct screening and treatment. While socioeconomic factors are known to be strongly associated with malaria burden, their specific impacts on malaria prevention behaviours during the 1,7-mRCTR implementation period remained unclear. This study aimed to construct a household wealth index and investigate its association with malaria prevention outcomes within the context of 1,7-mRCTR.Methods We used data from two cross-sectional household surveys conducted in 2015 (baseline) and 2018 (endline), covering 19 686 households. A 12-item wealth index was constructed using Mokken scale analysis, with weighted wealth scores calculated via multiple correspondence analysis to categorise households into wealth tertiles. Using logistic regression within a Difference-in-Differences (DID) framework, we assessed the association between household wealth and the household ownership of useful long-lasting insecticidal nets (LLINs), use of LLINs and use of antimalarial drugs.Results Analysis of the pooled data showed that households in the first (poorest) tertile had significantly lower odds of owing LLINs (OR=0.62, 95% CI 0.54 to 0.70, p<0.001) and using LLINs (OR=0.53, 95% CI 0.45 to 0.62, p<0.001) compared to the third (wealthiest) tertile. The DID analysis, accounting for the interaction between the intervention period (2018 vs 2015) and wealth tertile, showed a significantly greater increase in the odds of owing LLINs (OR=1.26, 95% CI 1.03 to 1.56) and using LLINs (OR=1.88, 95% CI 1.25 to 2.82) among households in the first tertile compared with the third tertile.Conclusion The wealth index effectively differentiated household socioeconomic status, revealing significant wealth-based disparities in malaria prevention behaviours. Importantly, the implementation of the 1,7-mRCTR approach appears to have had a disproportionately positive effect on poorer households, leading to a reduction in wealth-based inequalities related to key malaria prevention measures.",
  "authors": [
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China",
        "Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China"
      ],
      "name": "Chen Gao"
    },
    {
      "affiliations": [
        "Vanke School of Public Health, Tsinghua University, Beijing, China"
      ],
      "name": "Sikai Huang"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China"
      ],
      "name": "Haoyue Yin"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China"
      ],
      "name": "Shenning Lu"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China"
      ],
      "name": "Longsheng Liu"
    },
    {
      "affiliations": [
        "Environmental Health and Ecological Science Department, Ifakara Health Institute, Dar es Salaam, Tanzania"
      ],
      "name": "Yeromin P Mlacha"
    },
    {
      "affiliations": [
        "Environmental Health and Ecological Science Department, Ifakara Health Institute, Dar es Salaam, Tanzania"
      ],
      "name": "Prosper Chaki"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China",
        "School of Global Health, Chinese Centre for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China"
      ],
      "name": "Xiao-Nong Zhou"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China",
        "School of Global Health, Chinese Centre for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China"
      ],
      "name": "Ning Xiao"
    },
    {
      "affiliations": [
        "Vanke School of Public Health, Tsinghua University, Beijing, China"
      ],
      "name": "Sol Richardson"
    },
    {
      "affiliations": [
        "National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention",
        "Chinese Center for Tropical Diseases Research, Shanghai, China",
        "National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, China",
        "Key Laboratory on Parasite and Vector Biology, Ministry of Health, Shanghai, China",
        "WHO Centre for Tropical Diseases, Shanghai, China",
        "National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, China",
        "School of Global Health, Chinese Centre for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China"
      ],
      "name": "Duoquan Wang"
    }
  ],
  "title": "Development of a new wealth index for Tanzania: the moderated effect of the implementation of 1,7- malaria reactive community-based testing and response (1,7-mRCTR) by socioeconomic position (SEP) with malaria prevention",
  "uid": "944340bd-1883-5df1-9042-703445b739ae"
}