Andrea Bizzotto , Alfredo De Bellis , Valentina Marziano , Varvara A. Mouchtouri , Leonidas Kourentis , Lemonia Anagnostopoulos , Christos Hadjichristodoulou , Stefano Merler , Giorgio Guzzetta
{"title":"预测游轮上的诺如病毒病例,以支持船上的疫情管理。","authors":"Andrea Bizzotto , Alfredo De Bellis , Valentina Marziano , Varvara A. Mouchtouri , Leonidas Kourentis , Lemonia Anagnostopoulos , Christos Hadjichristodoulou , Stefano Merler , Giorgio Guzzetta","doi":"10.1016/j.tmaid.2025.102850","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Norovirus outbreaks on cruise ships are a significant threat to the cruising industry. Mathematical models have the potential to leverage routinely collected syndromic surveillance data on board to provide insight into outbreak evolution.</div></div><div><h3>Methods</h3><div>We used historical data from seven norovirus outbreaks occurred in 2011–2013, totalling 359 diagnosed cases, to assess the performance of automated forecasts in real-time. We compared the performance of a set of alternative models on three endpoints (the number of cases by symptom onset time, by diagnosis date, and the total number of cases until the end of the cruise), using the logarithmic score (logS), the ranked probability score (RPS), and the 95 % coverage.</div></div><div><h3>Results</h3><div>We found that the best forecasting performance was given by a model that includes both superspreading and the effect of case isolation. This model had in most cases a better score than that of a baseline model assuming constant incidence; this happened in 59–70 % of data points when assessed using the logS and 53–57 % with the RPS (depending on the considered endpoint). The best model also had the highest coverage over all endpoints. Its added value was especially evident for longer forecasting horizons, with an improvement in performance for up to 78 % of data points, both according to the logS and the RPS.</div></div><div><h3>Conclusions</h3><div>Simple mathematical models integrating key mechanisms of norovirus transmission can help predict the number of cases on board. This knowledge can be automatized in syndromic surveillance systems to support decision making for the management of outbreaks.</div></div>","PeriodicalId":23312,"journal":{"name":"Travel Medicine and Infectious Disease","volume":"65 ","pages":"Article 102850"},"PeriodicalIF":6.3000,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting norovirus cases on cruise ships to support outbreak management on board\",\"authors\":\"Andrea Bizzotto , Alfredo De Bellis , Valentina Marziano , Varvara A. Mouchtouri , Leonidas Kourentis , Lemonia Anagnostopoulos , Christos Hadjichristodoulou , Stefano Merler , Giorgio Guzzetta\",\"doi\":\"10.1016/j.tmaid.2025.102850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Norovirus outbreaks on cruise ships are a significant threat to the cruising industry. Mathematical models have the potential to leverage routinely collected syndromic surveillance data on board to provide insight into outbreak evolution.</div></div><div><h3>Methods</h3><div>We used historical data from seven norovirus outbreaks occurred in 2011–2013, totalling 359 diagnosed cases, to assess the performance of automated forecasts in real-time. We compared the performance of a set of alternative models on three endpoints (the number of cases by symptom onset time, by diagnosis date, and the total number of cases until the end of the cruise), using the logarithmic score (logS), the ranked probability score (RPS), and the 95 % coverage.</div></div><div><h3>Results</h3><div>We found that the best forecasting performance was given by a model that includes both superspreading and the effect of case isolation. This model had in most cases a better score than that of a baseline model assuming constant incidence; this happened in 59–70 % of data points when assessed using the logS and 53–57 % with the RPS (depending on the considered endpoint). The best model also had the highest coverage over all endpoints. Its added value was especially evident for longer forecasting horizons, with an improvement in performance for up to 78 % of data points, both according to the logS and the RPS.</div></div><div><h3>Conclusions</h3><div>Simple mathematical models integrating key mechanisms of norovirus transmission can help predict the number of cases on board. This knowledge can be automatized in syndromic surveillance systems to support decision making for the management of outbreaks.</div></div>\",\"PeriodicalId\":23312,\"journal\":{\"name\":\"Travel Medicine and Infectious Disease\",\"volume\":\"65 \",\"pages\":\"Article 102850\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Travel Medicine and Infectious Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1477893925000560\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Travel Medicine and Infectious Disease","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1477893925000560","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Forecasting norovirus cases on cruise ships to support outbreak management on board
Background
Norovirus outbreaks on cruise ships are a significant threat to the cruising industry. Mathematical models have the potential to leverage routinely collected syndromic surveillance data on board to provide insight into outbreak evolution.
Methods
We used historical data from seven norovirus outbreaks occurred in 2011–2013, totalling 359 diagnosed cases, to assess the performance of automated forecasts in real-time. We compared the performance of a set of alternative models on three endpoints (the number of cases by symptom onset time, by diagnosis date, and the total number of cases until the end of the cruise), using the logarithmic score (logS), the ranked probability score (RPS), and the 95 % coverage.
Results
We found that the best forecasting performance was given by a model that includes both superspreading and the effect of case isolation. This model had in most cases a better score than that of a baseline model assuming constant incidence; this happened in 59–70 % of data points when assessed using the logS and 53–57 % with the RPS (depending on the considered endpoint). The best model also had the highest coverage over all endpoints. Its added value was especially evident for longer forecasting horizons, with an improvement in performance for up to 78 % of data points, both according to the logS and the RPS.
Conclusions
Simple mathematical models integrating key mechanisms of norovirus transmission can help predict the number of cases on board. This knowledge can be automatized in syndromic surveillance systems to support decision making for the management of outbreaks.
期刊介绍:
Travel Medicine and Infectious Disease
Publication Scope:
Publishes original papers, reviews, and consensus papers
Primary theme: infectious disease in the context of travel medicine
Focus Areas:
Epidemiology and surveillance of travel-related illness
Prevention and treatment of travel-associated infections
Malaria prevention and treatment
Travellers' diarrhoea
Infections associated with mass gatherings
Migration-related infections
Vaccines and vaccine-preventable disease
Global policy/regulations for disease prevention and control
Practical clinical issues for travel and tropical medicine practitioners
Coverage:
Addresses areas of controversy and debate in travel medicine
Aims to inform guidelines and policy pertinent to travel medicine and the prevention of infectious disease
Publication Features:
Offers a fast peer-review process
Provides early online publication of accepted manuscripts
Aims to publish cutting-edge papers