The Importance of Epidemiological Surveillance
The early recognition of an epidemic outbreak is crucial for the prevention and control of illnesses. Health surveillance is a significant method of collection and analysis of the disease-related data (Zhang, Zhang, Young, & Li, 2014). The systems used for surveillance are designed to detect the abnormal incidence of infectious diseases and other health conditions. For example, the method of the time series models is significant for the prediction of epidemiological tendencies, as they use the historical data to detect the patterns of outbreaks (Zhang et al., 2014).
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To forecast in-hospital infections, researchers use the methods of exponential smoothing and generalized regression. Autoregressive integrated moving average models (ARIMA) are utilized for prediction of many serious conditions, including tuberculosis (Zhang et al., 2014). These methods are the most common means of epidemiological surveillance.
The utilization of surveillance methods underlines the importance of such measures of disease control and prevention for public health. Infectious diseases pose a threat to human health, and it is necessary to prevent their occurrence. Epidemiological surveillance systems allow researchers to suggest strategies for public health planning, including vaccination. Without them, it would not be possible to assess the disease morbidity and reduce the response time to outbreaks.
Moreover, epidemiological surveillance allows researchers to estimate the likely progression of the infection and the consequences of vaccination. For example, with the use of mathematical modeling, they can conclude what proportions of the population must be vaccinated to prevent the progression of the disease, what are the groups at risk, and what are the most common means of transmission of the infection. The findings of the surveillance are significant for public health, as they improve its level and ensure that there are strategies to protect individuals from possible contamination.
Epidemiological Surveillance and Bioterrorism
Bioterrorism involves the use of biological agents, including bacteria, fungi, viruses, and toxins, as weapons. Acts of bioterrorism can result in severe illnesses and deaths of humans and animals. There has been a rise in the number of bioterrorist attacks in the past twenty years, which means that it is crucial to assume measures of their prevention (Grundmann, 2014). Epidemiological surveillance can play a significant role in the management of these incidents, as it can prevent their occurrence in the future and eliminate the immediate threat they pose.
In this case, the surveillance can be performed by epidemiological investigations of an abnormally high rate of infections among a specific population or a sudden outbreak of symptoms with indications of an epidemic (Grundmann, 2014). They can be conducted through environmental surveillance with the use of sentinel air-measurement devices, as well as through laboratory tests and monitoring of clinical data.
It is crucial to point out that the earlier the dissemination of biological agents is detected, the lower the morbidity and mortality rates are. For example, if there were a bioterrorist attack during a large sporting event, epidemiological surveillance would be significant in the prevention of secondary contaminations of those having physical contact with the primarily affected group of people. Air-measurement devices could be used to indicate the agent utilized by bioterrorists and the means of its transmission. Surveillance would also help in the development of precautionary measures to prevent the severe effects of bioterrorist attacks in the future, as well as evaluate the risks of their occurrence under other circumstances.
Grundmann, O. (2014). The current state of bioterrorist attack surveillance and preparedness in the US. Risk Management and Healthcare Policy, 7, 177-187.
Zhang, X., Zhang, T., Young, A. A., & Li, X. (2014). Applications and comparisons of four time series models in epidemiological surveillance data. PLoS One, 9. Web.