Examine metadata for hospital search engines and other cyber/technology measures during covid-19 pandemic.

Covid-19 is among the world’s worst crises that killed hundreds of thousands of people around the globe. The pandemic has resulted in a significant loss of life worldwide and poses an extraordinary challenge to the health care system, food production, and the workplace. The pandemic’s social and economic instability is disastrous, exposing hundreds of thousands of people to abject poverty. Workers in the informal financial system were extremely vulnerable since the huge percentage lacked social welfare, access to quality medical services, and economic opportunities. The world health organization reported that several people could not feed themselves and their family members during lockdowns because they lacked the means to earn a living (Chriscaden, 2020). For most people, no income signifies no food, or at best, a little less nutritious food. The introduction of Covid-19 brought a breakthrough to the pandemic as it has reduced the rate of Covid-19 spread and eased the economy as people managed to return to their physical workplaces.

One other crisis that worsened the covid crises and delayed vaccination rates across the world was misinformation. Taking action based on incorrect information can be disastrous. According to the World Health Organization, “nearly 6 000 people were hospitalized around the world in the first three months of 2020 due to coronavirus misinformation” (WHO, 2020). It is reported that at least 800 individuals could have died due to COVID-19* misinformation during this period. The use of metadata and search engines could therefore help salvage the effects of misinformation. Since medical data on the Internet is generated by various organizations and individuals with wide variations of credibility, and its intended audience range from the general populace to medical practitioners, the quality and type of data available varies greatly. It is difficult for regular individuals to identify credible data relating to their medical conditions on the Internet in such a setting. Health portals, webpages that operate as conduits to other sites, and cumulative content from numerous sources and convey it to users have emerged to address this issue. This discussion analyzes literature on metadata for hospital search engines and other cyber/technology measures during the covid-19 pandemic.

In conclusion, metadata and search engines are essential in healthcare settings. The spread of fake news has immense negative implications on society as it can lead to the loss of property and even death, massive public panic, and even cause wars on nations. Based on the literature review above, misinformation has created uncertainty, leading people to deny COVID-19 vaccines, dismiss public health preventive metrics like masking and physical distancing, and use unconfirmed remedies. Highlighting core aspects engaged in the propagation of information is an essential step towards reducing the spread of misinformation. Several solutions were discussed, including graph theory and machine learning techniques, SA and opinion mining techniques, data mining algorithms and methodologies, and Google search traffic data. The literature review also concluded that Predicting COVID-19 incidence is necessary and possible through analysis of Google Trends Data. Metadata and search engines are also essential components of Infodemiological Study. Lastly, integrate viral sequences sources to provide a multilateral, cohesive framework for all data identifying sequences across various databases.