Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation.
Toor JBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Adams ERDepartment of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Aliee MMathematics Institute, University of Warwick, Coventry, United Kingdom.
Amoah BCentre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
Anderson RMLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Ayabina DBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Bailey RFaculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Basáñez MGLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Blok DJDepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Blumberg SFrancis I Proctor Foundation, University of California, San Francisco, California, United States of America.
Borlase ABig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Rivera RCDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
Castaño MSDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
Chitnis NDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
Coffeng LEDepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Crump REMathematics Institute, University of Warwick, Coventry, United Kingdom.
Das ADepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
Davis CNMathematics Institute, University of Warwick, Coventry, United Kingdom.
Davis ELBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Deiner MSFrancis I Proctor Foundation, University of California, San Francisco, California, United States of America.
Diggle PJCentre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
Fronterre CCentre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
Giardina FDepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Giorgi ECentre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
Graham MBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Hamley JIDLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Huang CIMathematics Institute, University of Warwick, Coventry, United Kingdom.
Kura KLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Lietman TMFrancis I Proctor Foundation, University of California, San Francisco, California, United States of America.
Lucas TCDBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Malizia VDepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Medley GFCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Meeyai ACentre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Michael EDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
Porco TCFrancis I Proctor Foundation, University of California, San Francisco, California, United States of America.
Prada JMSchool of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
Rock KSMathematics Institute, University of Warwick, Coventry, United Kingdom.
Le Rutte EADepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Smith MEDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
Spencer SEFZeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom.
Stolk WADepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Touloupou PDepartment of Statistics, University of Warwick, Coventry, United Kingdom.
Vasconcelos ABig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Vegvari CLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
de Vlas SJDepartment of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
Walker MLondon Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Hollingsworth TDBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
English
Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.