BibTex format
@article{Vasconcelos:2024:cid/ciae082,
author = {Vasconcelos, A and King, JD and Nunes-Alves, C and Anderson, R and Argaw, D and Basáñez, M-G and Bilal, S and Blok, DJ and Blumberg, S and Borlase, A and Brady, OJ and Browning, R and Chitnis, N and Coffeng, LE and Crowley, EH and Cucunubá, ZM and Cummings, DAT and Davis, CN and Davis, EL and Dixon, M and Dobson, A and Dyson, L and French, M and Fronterre, C and Giorgi, E and Huang, C-I and Jain, S and James, A and Kim, SH and Kura, K and Lucianez, A and Marks, M and Mbabazi, PS and Medley, GF and Michael, E and Montresor, A and Mutono, N and Mwangi, TS and Rock, KS and Saboyá-Díaz, M-I and Sasanami, M and Schwehm, M and Spencer, SEF and Srivathsan, A and Stawski, RS and Stolk, WA and Sutherland, SA and Tchuenté, L-AT and de, Vlas SJ and Walker, M and Brooker, SJ and Hollingsworth, TD and Solomon, AW and Fall, IS},
doi = {cid/ciae082},
journal = {Clinical Infectious Diseases},
pages = {S83--S92},
title = {Accelerating progress towards the 2030 neglected tropical diseases targets: how can quantitative modeling support programmatic decisions?},
url = {http://dx.doi.org/10.1093/cid/ciae082},
volume = {78},
year = {2024}
}
RIS format (EndNote, RefMan)
TY - JOUR
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.
AU - Vasconcelos,A
AU - King,JD
AU - Nunes-Alves,C
AU - Anderson,R
AU - Argaw,D
AU - Basáñez,M-G
AU - Bilal,S
AU - Blok,DJ
AU - Blumberg,S
AU - Borlase,A
AU - Brady,OJ
AU - Browning,R
AU - Chitnis,N
AU - Coffeng,LE
AU - Crowley,EH
AU - Cucunubá,ZM
AU - Cummings,DAT
AU - Davis,CN
AU - Davis,EL
AU - Dixon,M
AU - Dobson,A
AU - Dyson,L
AU - French,M
AU - Fronterre,C
AU - Giorgi,E
AU - Huang,C-I
AU - Jain,S
AU - James,A
AU - Kim,SH
AU - Kura,K
AU - Lucianez,A
AU - Marks,M
AU - Mbabazi,PS
AU - Medley,GF
AU - Michael,E
AU - Montresor,A
AU - Mutono,N
AU - Mwangi,TS
AU - Rock,KS
AU - Saboyá-Díaz,M-I
AU - Sasanami,M
AU - Schwehm,M
AU - Spencer,SEF
AU - Srivathsan,A
AU - Stawski,RS
AU - Stolk,WA
AU - Sutherland,SA
AU - Tchuenté,L-AT
AU - de,Vlas SJ
AU - Walker,M
AU - Brooker,SJ
AU - Hollingsworth,TD
AU - Solomon,AW
AU - Fall,IS
DO - cid/ciae082
EP - 92
PY - 2024///
SN - 1058-4838
SP - 83
TI - Accelerating progress towards the 2030 neglected tropical diseases targets: how can quantitative modeling support programmatic decisions?
T2 - Clinical Infectious Diseases
UR - http://dx.doi.org/10.1093/cid/ciae082
UR - https://www.ncbi.nlm.nih.gov/pubmed/38662692
UR - https://academic.oup.com/cid/article/78/Supplement_2/S83/7657829
UR - http://hdl.handle.net/10044/1/111696
VL - 78
ER -