[Risk assessment of global COVID-19 imported cases into China]

Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index

Background

Mainland China, the world's most populous region, experienced a large-scale coronavirus disease 2019 (COVID-19) outbreak in 2020 and 2021, respectively. Existing infodemiology studies have primarily concentrated on the prospective surveillance of confirmed cases or symptoms which met the criterion for investigators; nevertheless, the actual impact regarding COVID-19 on the public and subsequent attitudes of different groups towards the COVID-19 epidemic were neglected.

Methods

This study aimed to examine the public web-based search trends and behavior patterns related to COVID-19 outbreaks in mainland China by using hot words and Baidu Index (BI). The initial hot words (the high-frequency words on the Internet) and the epidemic data (2019/12/01-2021/11/30) were mined from infodemiology platforms. The final hot words table was established by two-rounds of hot words screening and double-level hot words classification. Temporal distribution and demographic portraits of COVID-19 were queried by search trends service supplied from BI to perform the correlation analysis. Further, we used the parameter estimation to quantitatively forecast the geographical distribution of COVID-19 in the future.

Results

The final English-Chinese bilingual table was established including six domains and 32 subordinate hot words. According to the temporal distribution of domains and subordinate hot words in 2020 and 2021, the peaks of searching subordinate hot words and COVID-19 outbreak periods had significant temporal correlation and the subordinate hot words in COVID-19 Related and Territory domains were reliable for COVID-19 surveillance. Gender distribution results showed that Territory domain (the male proportion: 67.69%; standard deviation (SD): 5.88%) and Symptoms/Symptom and Public Health (the female proportion: 57.95%, 56.61%; SD: 0, 9.06%) domains were searched more by male and female groups respectively. The results of age distribution of hot words showed that people aged 20-50 (middle-aged people) had a higher online search intensity, and the group of 20-29, 30-39 years old focused more on Media and Symptoms/Symptom (proportion: 45.43%, 51.66%; SD: 15.37%, 16.59%) domains respectively. Finally, based on frequency rankings of searching hot words and confirmed cases in Mainland China, the epidemic situation of provinces and Chinese administrative divisions were divided into 5 levels of early-warning regions. Central, East and South China regions would be impacted again by the COVID-19 in the future.

Developing and testing of an Early Warning mobileHealth screening and risk scoring application for preventing heath worker in-hospital transmission of Covid-19: A feasibility study

BACKGROUND

Hospitals have been identified as very high-risk places for Covid-19 transmission between health workers and non-covid-19 patients. Health care workers are the most at risk population to contract and transmit the infection especially to the already vulnerable non-Covid-19 patients. In Low-income countries, routine testing is not feasible due to the high cost of testing therefore presenting the risk of un-controlled transmission within the non Covid-19 treatment wards. This challenge necessitated the development of an affordable intermediary screening tool that would enable early identification of potentially infected health care workers and for early real time DNA-PCR testing prioritization. This would limit the contact time of potentially infected health care workers with the patients but also efficiently utilize the limited testing kits.

OBJECTIVE

To describe an early warning in-hospital risk analysis mobile application for screening Covid-19 and determine the feasibility and user friendliness among health care workers.

METHODS

Materials and methods: Using the WHO, Ministry of Health of Uganda guidelines on the case definition of Covid-19, we developed a screening questionnaire tool for risk assessment of Covid-19. Specific signs and symptoms were weighted based on how prevalent they were among Covid-19 patients and subsequently an algorithm developed for the various case scenarios of Covid-19. Risk sores were computed based on the symptoms and contact history and a daily risk category assigned based on the risk score. The questionnaire, flow charts and algorithms were then integrated into an android mobile application. Following the launch, 100 health care workers in the directorate of surgical services used the application for one month and the feasibility and consistence of use as well as user friendliness was evaluated. Health care workers would submit their daily risk scores and high-risk staff would be selected for testing and further intervention including treatment.

RESULTS

Results: The primary result of this research project was the development of a mobile based daily early warning system for in-hospital transmission of Covid-19. Overall, the EWAS mobile application was found to be feasible with over 69% of the health care workers having logged more than 67% of the required times. Over 93% of the participants reported the tool as easy to use.

CONCLUSIONS

Conclusion: The EWAS mobile application is a feasible and user-friendly daily risk scoring tool for preventing in-hospital transmission of Covid-19. Despite it, not being designed to be a diagnostic but a screening tool, there is a need to evaluate its sensitivity in predicting persons likely to have contracted Covid-19.

CLINICALTRIAL

The Epidemiology of COVID-19 in the Gansu and Jinlin Provinces, China

The COVID-19 outbreak has become a pandemic. The outbreak was able to be controlled in China by mid-April through the implementation of critical measures; however, significant reverse transmission has resulted in hot spots perturbing prevention and control. To date, there have only been a total of 92 indigenous COVID-19 cases confirmed in the Gansu Province, which is considered to be a consequence of the strict screening approach applied during the outbreak. The emergency response level to COVID-19 were able to be decreased from high to low, despite some relatively minor reverse transmission cases from other countries in March 2020. The stringent preparative measures undertaken by the Gansu authorities, involving high-level, streamlined cooperation between the transportation, quarantine, and medical resource departments, have underpinned this success. There has been an emergence of clusters of freshly infected COVID-19 patients in the Jilin Province in northeast China. The single largest cluster has been in Shulan of the Jilin Province, involving 43 confirmed infections. A strict lockdown was implemented immediately. The source of the current outbreak of COVID-19 is suggested to be travelers returning from Russia. The current strategy from the Chinese authorities is aimed at preventing reverse transmission via international importation to avert a rebound of COVID-19 in China. These data highlight the need for an exceptionally high level of vigilance and for a pre-emptive response that is informative for the development of policy to prevent a second and further waves of infections in general.