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 Dixon; Andrew 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

doi:10.1093/cid/ciae082

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 journal › Article › peer-review

2 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	S83-S92
Journal	Clinical Infectious Diseases
Volume	78
Issue number	Supplement_2
DOIs	https://doi.org/10.1093/cid/ciae082
State	Published - May 15 2024

All Science Journal Classification (ASJC) codes

Microbiology (medical)
Infectious Diseases

Keywords

control
elimination
mathematical models
neglected tropical diseases
policy-making

Access to Document

10.1093/cid/ciae082

Cite this

Vasconcelos, A., King, J. D., Nunes-Alves, C., Anderson, R., Argaw, D., Basáñez, M. G., Bilal, S., Blok, D. J., Blumberg, S., Borlase, A., Brady, O. J., Browning, R., Chitnis, N., Coffeng, L. E., Crowley, E. H., Cucunubá, Z. M., Cummings, D. A. T., Davis, C. N., Davis, E. L., ... Fall, I. S. (2024). Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions? Clinical Infectious Diseases, 78(Supplement_2), S83-S92. https://doi.org/10.1093/cid/ciae082

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

abstract = "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.",

keywords = "control, elimination, mathematical models, neglected tropical diseases, policy-making",

author = "Andreia Vasconcelos and King, {Jonathan D.} and Cl{\'a}udio Nunes-Alves and Roy Anderson and Daniel Argaw and Bas{\'a}{\~n}ez, {Maria Gloria} and Shakir Bilal and Blok, {David J.} and Seth Blumberg and Anna Borlase and Brady, {Oliver J.} and Raiha Browning and Nakul Chitnis and Coffeng, {Luc E.} and Crowley, {Emily H.} and Cucunub{\'a}, {Zulma M.} and Cummings, {Derek A.T.} and Davis, {Christopher Neil} and Davis, {Emma Louise} and Matthew Dixon and Andrew Dobson and Louise Dyson and Michael French and Claudio Fronterre and Emanuele Giorgi and Huang, {Ching I.} and Saurabh Jain and Ananthu James and Kim, {Sung Hye} and Klodeta Kura and Ana Lucianez and Michael Marks and Mbabazi, {Pamela Sabina} and Medley, {Graham F.} and Edwin Michael and Antonio Montresor and Nyamai Mutono and Mwangi, {Thumbi S.} and Rock, {Kat S.} and Saboy{\'a}-D{\'i}az, {Martha Idal{\'i}} and Misaki Sasanami and Markus Schwehm and Spencer, {Simon E.F.} and Ariktha Srivathsan and Stawski, {Robert S.} and Stolk, {Wilma A.} and Sutherland, {Samuel A.} and Tchuente, {Louis Albert Tchuem} and {De Vlas}, {Sake J.} and Martin Walker and Brooker, {Simon J.} and Hollingsworth, {T. Deirdre} and Solomon, {Anthony W.} and Fall, {Ibrahima Soce}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s). Published by Oxford University Press on behalf of Infectious Diseases Society of America.",

year = "2024",

month = may,

day = "15",

doi = "10.1093/cid/ciae082",

language = "English (US)",

volume = "78",

pages = "S83--S92",

journal = "Clinical Infectious Diseases",

issn = "1058-4838",

publisher = "Oxford University Press",

number = "Supplement_2",

}

Vasconcelos, A, King, JD, Nunes-Alves, C, Anderson, R, Argaw, D, Basáñez, MG, Bilal, S, Blok, DJ, Blumberg, S, Borlase, A, Brady, OJ, Browning, R, Chitnis, N, Coffeng, LE, Crowley, EH, Cucunubá, ZM, Cummings, DAT, Davis, CN, Davis, EL, Dixon, M, Dobson, A, Dyson, L, French, M, Fronterre, C, Giorgi, E, Huang, CI, Jain, S, James, A, Kim, SH, Kura, K, Lucianez, A, Marks, M, Mbabazi, PS, Medley, GF, Michael, E, Montresor, A, Mutono, N, Mwangi, TS, Rock, KS, Saboyá-Díaz, MI, Sasanami, M, Schwehm, M, Spencer, SEF, Srivathsan, A, Stawski, RS, Stolk, WA, Sutherland, SA, Tchuente, LAT, De Vlas, SJ, Walker, M, Brooker, SJ, Hollingsworth, TD, Solomon, AW & Fall, IS 2024, 'Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?', Clinical Infectious Diseases, vol. 78, no. Supplement_2, pp. S83-S92. https://doi.org/10.1093/cid/ciae082

TY - JOUR

T1 - Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets

T2 - How Can Quantitative Modeling Support Programmatic Decisions?

AU - Vasconcelos, Andreia

AU - King, Jonathan D.

AU - Nunes-Alves, Cláudio

AU - Anderson, Roy

AU - Argaw, Daniel

AU - Basáñez, Maria Gloria

AU - Bilal, Shakir

AU - Blok, David J.

AU - Blumberg, Seth

AU - Borlase, Anna

AU - Brady, Oliver J.

AU - Browning, Raiha

AU - Chitnis, Nakul

AU - Coffeng, Luc E.

AU - Crowley, Emily H.

AU - Cucunubá, Zulma M.

AU - Cummings, Derek A.T.

AU - Davis, Christopher Neil

AU - Davis, Emma Louise

AU - Dixon, Matthew

AU - Dobson, Andrew

AU - Dyson, Louise

AU - French, Michael

AU - Fronterre, Claudio

AU - Giorgi, Emanuele

AU - Huang, Ching I.

AU - Jain, Saurabh

AU - James, Ananthu

AU - Kim, Sung Hye

AU - Kura, Klodeta

AU - Lucianez, Ana

AU - Marks, Michael

AU - Mbabazi, Pamela Sabina

AU - Medley, Graham F.

AU - Michael, Edwin

AU - Montresor, Antonio

AU - Mutono, Nyamai

AU - Mwangi, Thumbi S.

AU - Rock, Kat S.

AU - Saboyá-Díaz, Martha Idalí

AU - Sasanami, Misaki

AU - Schwehm, Markus

AU - Spencer, Simon E.F.

AU - Srivathsan, Ariktha

AU - Stawski, Robert S.

AU - Stolk, Wilma A.

AU - Sutherland, Samuel A.

AU - Tchuente, Louis Albert Tchuem

AU - De Vlas, Sake J.

AU - Walker, Martin

AU - Brooker, Simon J.

AU - Hollingsworth, T. Deirdre

AU - Solomon, Anthony W.

AU - Fall, Ibrahima Soce

PY - 2024/5/15

Y1 - 2024/5/15

N2 - 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.

AB - 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.

KW - control

KW - elimination

KW - mathematical models

KW - neglected tropical diseases

KW - policy-making

UR - http://www.scopus.com/inward/record.url?scp=85191415855&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85191415855&partnerID=8YFLogxK

U2 - 10.1093/cid/ciae082

DO - 10.1093/cid/ciae082

M3 - Article

C2 - 38662692

AN - SCOPUS:85191415855

SN - 1058-4838

VL - 78

SP - S83-S92

JO - Clinical Infectious Diseases

JF - Clinical Infectious Diseases

IS - Supplement_2

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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