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Table 2 Characteristics of publications – Observational and surveillance studies (N = 12)

From: Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review

First author, year Infection   Population Model   Main outcome Design outcome(s) Remarks
  Epidemiological category Name   Typea Structured/Networkb    
Graat, 2001 [16] Animal Bovine herpesvirus 1 Cattle farming Compartmental - deterministic Yes/No Reproduction ratio between herds - Frequency - Sample size
Michael, 2006 [17] Human, vector-borne Lymphatic filariasis Not described Compartmental – deterministicc No/No Prevalence of microfilaraemia - Frequency - Sample size - Monitoring - Power
Savill, 2008 [18] Animal Avian influenza Commercial poultry flocks (The Netherlands) IBM Yes/No False alarm rate - Monitoring
Arnold, 2013 [19] Animal Avian influenza Poultry farming IBM Yes/Yes Size and duration of an outbreak - Sample size - Whom Spatial model
Smieszek, 2013 [20] Human, respiratory Influenza An US high school (teachers, students, staff) IBM Yes/Yes Performance of collocation ranking - Sample size - Whom
Ciccolini, 2014 [21] Human, nosocomial Nosocomial pathogens Acute hospitals (England, The Netherlands) Compartmental - stochastic Yes/Yes Time to detection and number of infected hospitals - Sample size - Whom
Gonzales, 2014 [22] Animal Avian influenza Layer chickens (The Netherlands) Compartmental - deterministic Yes/No Required sample size and frequency for early detection - Frequency - Number - Sample size
Leslie, 2014 [23] Animal Classical swine fever Wild pig, Kimberley region (Australia) IBMc Yes/Yes Epidemic length, number of days to complete the surveillance, number of cells sampled, number of groups to be sampled - Sample size - Whom A within-herd model combined with a spatial between-herd model
Mizumoto, 2014 [24] Human, vector borne Dengue virus Not described Compartmental - deterministic Yes/No Relative risk of severe dengue and ‘dengue hemorrhagic fever’/ ‘dengue shock syndrome’ during secondary infection - Timing of sampling
Pinsent, 2014 [25] Animal Avian influenza Commercial poultry barns Compartmental - deterministic No/No Estimates of basic reproduction number and time of virus introduction - Frequency - Sample size
van Bunnik, 2015 [26] Human, nosocomial Meticillin-resistant Staphylococcus aureus Hospitals (Scotland) Compartmental - stochastic Yes/Yes Time until first detection of new health-care associated infection - Sample size - Whom Similar model as Ciccolini, 2012
Vinh, 2015 [27] Human, respiratory Influenza General population Compartmental - deterministic No/No Statistical identifiability of antibody generation, antibody waning, and reinfection - Frequency - Sample size - Power
  1. amodel type: IBM – individual based model; b structured: population structure is reflected in model, network: network of contacts between individuals is explicitly modelled; c model type obtained from the original article