{
  "abstract": "Introduction Accurate mosquito surveillance is essential for guiding targeted interventions. To capture the spatial and temporal heterogeneity of mosquito populations, surveillance designs would ideally be flexible and evidence-based, that is, informed by prior data. This study compares a newly developed entomological adaptive surveillance framework (EASF) and routine entomological surveillance in Ghana and Mozambique. Routine surveillance refers to standard practices by National Malaria Control Programmes, while EASF enables the strategic selection of sampling locations based on modelled risk or environmental criteria. The study evaluates both approaches based on Anopheles mosquito catch rates, model predictive performance and the proportion of obsolete sampling locations—those contributing little to overall surveillance outcomes and model improvement.Methods A Bayesian framework for exceedance probability is employed in this adaptive design to select the number and location of the adaptive sites. Estimates are based on a Bayesian spatiotemporal model with nugget effects to analyse mosquito abundance, using log-transformed counts to address heavy-tailed distributions.Results The EASF outperformed routine surveillance in most metrics, including mosquito catch rates, model robustness and reduction in uncertainty. Notably, when standardised, EASF sites yielded higher mosquito catches and more stable predictions, as indicated by lower coefficients of variation. While EASF generally improved model inference and predictive accuracy, performance varied by country. Nevertheless, EASF consistently identified proportionally fewer obsolete locations than routine surveillance, demonstrating its efficiency in targeting informative sites.Conclusions EASF offers an effective, evidence-based approach to improving surveillance precision, enabling surveillance programmes to dynamic transmission systems and emerging needs while maintaining operational feasibility. Integrating adaptive and routine designs can enhance surveillance efficiency, either by improving accuracy, reducing site numbers or accelerating detection of ecological changes. The key to effective entomological surveillance is not rigidly achieving a target, but continuously adapting towards it.",
  "authors": [
    {
      "affiliations": [
        "Lancaster Ecology and Epidemiology Group, Lancaster Medical School, Lancaster University, Lancaster, UK"
      ],
      "name": "Luigi Sedda"
    },
    {
      "affiliations": [
        "Lancaster Ecology and Epidemiology Group, Lancaster Medical School, Lancaster University, Lancaster, UK"
      ],
      "name": "Abdollah Jalilian"
    },
    {
      "affiliations": [
        "Malaria Elimination Initiative, Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA",
        "Centro de Investigação em Saúde de Manhiça, Manhica, Maputo Province, Mozambique"
      ],
      "name": "Mercy Opiyo"
    },
    {
      "affiliations": [
        "Malaria Elimination Initiative, Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA"
      ],
      "name": "Steven Gowelo"
    },
    {
      "affiliations": [
        "Programa Nacional de Controlo da Malária, Ministerio da Saude, Maputo, Maputo City, Mozambique"
      ],
      "name": "Dulcisária J Marrenjo"
    },
    {
      "affiliations": [
        "National Malaria Elimination Programme, Ghana Ministry of Health, Accra, Greater Accra Region, Ghana"
      ],
      "name": "Christian Atta-Obeng"
    },
    {
      "affiliations": [
        "National Malaria Elimination Programme, Ghana Ministry of Health, Accra, Greater Accra Region, Ghana"
      ],
      "name": "Ernest Boampong"
    },
    {
      "affiliations": [
        "National Malaria Elimination Programme, Ghana Ministry of Health, Accra, Greater Accra Region, Ghana"
      ],
      "name": "Samuel K Oppong"
    },
    {
      "affiliations": [
        "National Malaria Elimination Programme, Ghana Ministry of Health, Accra, Greater Accra Region, Ghana"
      ],
      "name": "Otubea Owusu-Akrofi"
    },
    {
      "affiliations": [
        "Malaria Elimination Initiative, Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA"
      ],
      "name": "Edward Thomsen"
    },
    {
      "affiliations": [
        "Malaria Elimination Initiative, Institute for Global Health Sciences, University of California San Francisco, San Francisco, California, USA"
      ],
      "name": "Allison Tatarsky"
    },
    {
      "affiliations": [
        "National Malaria Elimination Programme, Ghana Ministry of Health, Accra, Greater Accra Region, Ghana"
      ],
      "name": "Keziah L Malm"
    },
    {
      "affiliations": [
        "Programa Nacional de Controlo da Malária, Ministerio da Saude, Maputo, Maputo City, Mozambique"
      ],
      "name": "Baltazar Candrinho"
    },
    {
      "affiliations": [
        "University of Notre Dame, Notre Dame, Indiana, USA"
      ],
      "name": "Neil F Lobo"
    }
  ],
  "title": "Evaluation of the Entomological Adaptive Surveillance Framework for malaria vector monitoring: a comparative field trial with routine surveillance in Ghana and Mozambique",
  "uid": "c6384b83-dad8-5063-9e7e-b21bc9b5072b"
}