Table 1.

Routes to assessing public health and infectious disease surveillance techniques with advantages and disadvantages.

Technique	Examples	Advantages	Disadvantages	References
Sentinel Surveillance	General practitioner’s (GPs) reporting cases of influenza	Making use of an efficient system that is already in place Increase communication within communities Can help detecting larger health problems in a population	Rare and novel microbes occurrences are likely to be missed, e.g. new emerging virus Often focus on specific diseases	(Lee et al., 2010)
Clinical-based surveillance		Increased knowledge transfer between epidemiologists and microbiology laboratories Detailed information found on specific details of microbe e.g. virulence Online reporting available for specific diseases and up-to-date global databases publically available e.g. FluNet from WHO (https://www.who.int/influenza/gisrs_laboratory/flunet/en/)	Requires significant facilities, resources, trained staff and good communication links. Central reference laboratory is needed for standardisation and support If pathogens are rare, can lead to staff being complacent Selection bias on which samples are sent to the laboratory	(Choi, 2012)
Questionnaires or surveys	Recurrent or cross-sectional surveys	Can collect data for multiple diseases or exposures at one time Capability for local, national or international level Standardised methods utilised and high quality data often obtained Flexibility in questions asked Build up trends if survey is done repeatedly	Bias More information about public health Expensive – costs will vary on sample size, time period of survey Time delay to results If optional might not get a good response – might not be representative of whole populations Results can be difficult to interpret	(Thacker and Berkelman, 1988)
Search engine trends	Google Flu Trends (http://google.com/trends/)	Rapid obtainment of results Effective for large populations of web users Potential to track epidemics or diseases with high prevalence in a population	Difficult to determine if individuals searching are having symptoms or googling as concerned or to find out more Requires internet access, not as suitable for developing countries Differences in language backgrounds can lead to different words to describe symptoms being googled Diseases with low prevalence won’t spike enough to notice	(Carneiro and Mylonakis, 2009)
Mortality and morbidity rates	Deaths recorded for diseases like Ebola or influenza	Inexpensive and well-established system of reporting Death certificates are legally required in most countries Can aid in monitoring the progression of an epidemic	If deaths from a particular cause are too low, mortality statistics potentially don’t reflect accurate incidence of the disease Long delays in getting results Significant variation into how death certificates are filled Passive form of surveillance	(Choi, 2012)
Hospital admission data	ED-based surveillance for The Emerging Infectious Disease Surveillance Network	Can provide data on severity of injury, new emerging infectious disease and drug abuse Help identify if changes in healthcare are needed Potential early flagging of bioterrorism attack	Significant human and resource investment for setting up system and connecting with public health system Confidentiality challenges in sharing information to public health agencies Compliance of often busy emergency department staff to fill in data Need to standardise data collection	(Hirshon, 2000)
Prescription Rates		Generate trends of dug patterns in a community	Prescription data not always easily accessible Potential under-representation of what’s being used -Over-the-counter drugs -Prescription medications can be bought without prescription -Hospital data is not captured Cannot know if patient has taken drug	(Cadarette and Wong, 2015)
Human bio-monitoring	Assess an environmental exposure of a toxin	Information received detailed and of high quality Can assess suspected exposure of an individual If collected repeatedly can build up exposure pattern over time.	Small focus group – might not be representative of a large population Selection of control group is challenging Lengthy ethical considerations, samples collected must be used for specific research project – further approval and consent needed for new analysis	(Bauer, 2008, Needham et al., 2007)
Wastewater-based Epidemiology	Assess exposure to chemicals at the community level	Capable of spatial and temporal trends Data in near-real time (potential for real time with biosensors) Information given on whole population Ethical considerations, does not require approval depending on size of urban area	Selection of biomarkers can be challenging Biomarker stability in wastewater Uncertainties related to contributing population and wastewater flows Significant time-lag between data collection and analysis	(Been et al., 2017, Choi et al., 2019, Lopardo et al., 2018, Rousis et al., 2017)