Detecting and characterizing disease outbreaks requires enormous amounts of time, skill and knowledge. But even after the most advanced tools are deployed, infectious diseases can still cause widespread illness and death. The last few decades have awakened scientists to the fact that advances in disease control cannot completely conquer infectious diseases. Outbreaks of previously “controlled” diseases such as plague (Madagascar), diphtheria (Bangladesh), Ebola (West Africa), and monkeypox (Nigeria) illustrate that disease control remains a challenging task.
Outbreaks of unknown illnesses affecting humans and animals occur regularly around the world. Many of these outbreaks are not formally reported because the symptoms do not fit the criteria for a disease under national notifiable disease systems designed to identify only diseases with known causes. Open-source syndromic surveillance is one tool to fill this gap in global health surveillance.
Although the COVID-19 pandemic is over, people remain concerned about its mutability, its effects on their family members and friends, the loss of their livelihoods and their financial difficulties, social stigma and discrimination, and their ability to perform daily activities. Some are also worried about the impact of future pandemics on their personal and professional lives.
Outbreaks can be caused by a variety of factors, including fear of infection, quarantine restrictions, school closures, and shortages of essential supplies. In addition, women, those living alone, those with a history of mental illness and substance abuse, and the elderly may have a greater risk for depression and anxiety [12–15]. The COVID-19 virus varies between populations due to different mutations, with type A largely found in North America and Australia and type B mainly in China and East Asia.