Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Andreia Vasconcelos, Jonathan D. King, Cláudio Nunes-Alves, Roy Anderson, Daniel Argaw, Maria Gloria Basáñez, Shakir Bilal, David J. Blok, Seth Blumberg, Anna Borlase, Oliver J. Brady, Raiha Browning, Nakul Chitnis, Luc E. Coffeng, Emily H. Crowley, Zulma M. Cucunubá, Derek A.T. Cummings, Christopher Neil Davis, Emma Louise Davis, Matthew DixonAndrew Dobson, Louise Dyson, Michael French, Claudio Fronterre, Emanuele Giorgi, Ching I. Huang, Saurabh Jain, Ananthu James, Sung Hye Kim, Klodeta Kura, Ana Lucianez, Michael Marks, Pamela Sabina Mbabazi, Graham F. Medley, Edwin Michael, Antonio Montresor, Nyamai Mutono, Thumbi S. Mwangi, Kat S. Rock, Martha Idalí Saboyá-Díaz, Misaki Sasanami, Markus Schwehm, Simon E.F. Spencer, Ariktha Srivathsan, Robert S. Stawski, Wilma A. Stolk, Samuel A. Sutherland, Louis Albert Tchuem Tchuente, Sake J. De Vlas, Martin Walker, Simon J. Brooker, T. Deirdre Hollingsworth, Anthony W. Solomon, Ibrahima Soce Fall

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

Original languageEnglish (US)
Pages (from-to)S83-S92
JournalClinical Infectious Diseases
Issue numberSupplement_2
StatePublished - May 15 2024

All Science Journal Classification (ASJC) codes

  • Microbiology (medical)
  • Infectious Diseases


  • control
  • elimination
  • mathematical models
  • neglected tropical diseases
  • policy-making


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