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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