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Human Health Studies
Published in Barry L. Johnson, Impact of Hazardous Waste on Human Health, 2020
Surveillance Systems: Public health surveillance is defined as “…the ongoing, systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know…” (Thacker and Berkelman, 1992). As used by public health practitioners, a surveillance system refers to a data-collecting system that monitors the occurrence of a specific disease (disease surveillance) or the distribution of exposure to potential hazards (hazard surveillance). An example of a disease surveillance system is the reporting to some state health departments by physicians and hospitals of cases of cancer or birth defects in newborn infants. Surveillance systems provide an early warning of situations in which epidemiologic investigations or other public health actions should be taken.
Fundamentals of Environmental Health Policymaking
Published in Barry L. Johnson, Maureen Y. Lichtveld, Environmental Policy and Public Health, 2017
Barry L. Johnson, Maureen Y. Lichtveld
Surveillance can be defined as a data collection system that monitors the occurrence of disease (disease surveillance) or the distribution of hazard (hazard surveillance). Such systems are the eyes and ears of public health practice. Surveillance systems typically collect data from individual health care providers, hospitals, and entities such as health maintenance organizations. For example, state-based surveillance of birth defects and reproductive disorders has emerged, principally by way of federal grants. Other examples include surveillance of blood lead levels in children and, in some states, workers. These kinds of birth defects and blood lead data are typically collected by county and municipal health departments, reported to them by individual physicians, hospitals, and other health care providers.
Estimation and outbreak detection with interval observers for uncertain discrete-time SEIR epidemic models
Published in International Journal of Control, 2020
About 31.1 million to 43.9 million people were living with HIV in 2017 (World Health Organization, 2018), while seasonal influenza epidemics usually cause three to five million cases of severe illness and result in about 250,000 to 500,000 deaths worldwide every year, according to the World Health Organization (Vaillant, La Ruche, Tarantola, & Barboza, 2009). Infectious disease surveillance plays a major role in analysing the origins, dynamics and spread of such epidemics. Public Health Services (PHS) rely on surveillance data, e.g. records of infected people collected by agencies such as the Centers for Disease Control and Prevention in the United States, to estimate these infectious diseases' activity levels, prepare intervention strategies and design policy recommendations.
Using geospatial social media data for infectious disease studies: a systematic review
Published in International Journal of Digital Earth, 2023
Fengrui Jing, Zhenlong Li, Shan Qiao, Jiajia Zhang, Banky Olatosi, Xiaoming Li
Infectious disease surveillance is essential for identifying public health threats and developing prevention and control strategies. Key aspects of surveillance are the assessment of spatiotemporal patterns of specific disease transmission and the assessment of responses to public health emergencies caused by infectious diseases, such as individual attitudes, government policies, and vaccine efficacy. In this section, we summarized the efforts in assessing spatiotemporal patterns of and responses to infectious diseases using GSM data in Table 1.
Biosafety and biosecurity in Synthetic Biology: A review
Published in Critical Reviews in Environmental Science and Technology, 2019
Lucía Gómez-Tatay, José M. Hernández-Andreu
The NAS report argues that Synthetic Biology poses some challenges to the current strategies for determining if a health threat has arisen naturally or by means of an intentional attack and, in the second case, to attribute the attack to the actor responsible. These strategies include epidemiology, laboratory diagnostics, environmental monitoring, disease surveillance and agent identification. Among the new challenges that Synthetic Biology poses in this regard, the report identifies the possibility of developing bioweapons that produce health effects that cannot be immediately associated with a disease outbreak or attack (e.g. by reducing immunity or modifying the human microbiome). Additionally, Synthetic Biology could produce pathogens or toxins that are very different from any known natural agent, making it difficult or even impossible to identify the cause in a biological attack due to a lack of a comparator: “it would not be possible to act to mitigate or contain an outbreak until patients have developed symptoms that trigger a health community response; as a result of this delay, people would become ill before it is possible to know that an attack has occurred” (National Academies of Sciences, 2018). In this regard, MacIntyre (2015) explains that in recent years infectious diseases such as Ebola, Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and avian influenza have emerged following suspicious patterns, although natural emergence has always been assumed. In 1984, 751 people became ill with Salmonella in Oregon in the US, in what was initially believed to be a food-borne outbreak caused by unsanitary food handlers. However, a local politician accused a local religious cult of deliberately contaminating salad bars. Health authorities did not believe him, but six months later, the leader of the cult confessed to the attack. The case did not appear in medical literature until 13 years after the incident (Török et al., 1997).