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Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation.

  • Toor J Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Adams ER Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
  • Aliee M Mathematics Institute, University of Warwick, Coventry, United Kingdom.
  • Amoah B Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Anderson RM London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • Ayabina D Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Bailey R Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Basáñez MG London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • Blok DJ Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Blumberg S Francis I Proctor Foundation, University of California, San Francisco, California, United States of America.
  • Borlase A Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Rivera RC Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
  • Castaño MS Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
  • Chitnis N Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
  • Coffeng LE Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Crump RE Mathematics Institute, University of Warwick, Coventry, United Kingdom.
  • Das A Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
  • Davis CN Mathematics Institute, University of Warwick, Coventry, United Kingdom.
  • Davis EL Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Deiner MS Francis I Proctor Foundation, University of California, San Francisco, California, United States of America.
  • Diggle PJ Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Fronterre C Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Giardina F Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Giorgi E Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Graham M Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Hamley JID London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • Huang CI Mathematics Institute, University of Warwick, Coventry, United Kingdom.
  • Kura K London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • Lietman TM Francis I Proctor Foundation, University of California, San Francisco, California, United States of America.
  • Lucas TCD Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Malizia V Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Medley GF Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Meeyai A Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Michael E Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
  • Porco TC Francis I Proctor Foundation, University of California, San Francisco, California, United States of America.
  • Prada JM School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Rock KS Mathematics Institute, University of Warwick, Coventry, United Kingdom.
  • Le Rutte EA Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Smith ME Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
  • Spencer SEF Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom.
  • Stolk WA Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Touloupou P Department of Statistics, University of Warwick, Coventry, United Kingdom.
  • Vasconcelos A Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
  • Vegvari C London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • de Vlas SJ Department of Public Health, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Walker M London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
  • Hollingsworth TD Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
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  • 2020-09-28
Published in:
  • Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. - 2020
neglected tropical diseases
coronavirus
modeling
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.
Language
  • English
Open access status
hybrid
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https://sonar.ch/global/documents/232015
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