Seeing Like a State, Enacting Like an Algorithm: (Re)assembling Contact Tracing and Risk Assessment during the COVID-19 Pandemic

Predicting Success in the Embryology Lab: The Use of Algorithmic Technologies in Knowledge Production

This article analyzes local algorithmic practices resulting from the increased use of time-lapse (TL) imaging in fertility treatment. The data produced by TL technologies are expected to help professionals pick the best embryo for implantation. The emergence of TL has been characterized by promissory discourses of deeper embryo knowledge and expanded selection standardization, despite professionals having no conclusive evidence that TL improves pregnancy rates. Our research explores the use of TL tools in embryology labs. We pay special attention to standardization efforts and knowledge-creation facilitated through TL and its incorporated algorithms. Using ethnographic data from five UK clinical sites, we argue that knowledge generated through TL is contingent upon complex human-machine interactions that produce local uncertainties. Thus, algorithms do not simply add medical knowledge. Rather, they rearrange professional practice and expertise. Firstly, we show how TL changes lab routines and training needs. Secondly, we show that the human input TL requires renders the algorithm itself an uncertain and situated practice. This, in turn, raises professional questions about the algorithm's authority in embryo selection. The article demonstrates the embedded nature of algorithmic knowledge production, thus pointing to the need for STS scholarship to further explore the locality of algorithms and AI.

Would COVID-19 vaccination willingness increase if mobile technologies prohibit unvaccinated individuals from public spaces? A nationwide discrete choice experiment from China

BACKGROUND

Achieving COVID-19 community protection (aka, herd immunity) in China may be challenging because many individuals remain unsure or are unwilling to be vaccinated. One potential means to increase COVID-19 vaccine uptake is to essentially mandate vaccination by using existing mobile technologies that can prohibit unvaccinated individuals from certain public spaces. The "Health Code" is a ubiquitous mobile phone app in China that regulates freedom of travel based on individuals' predicted risk of exposure to SARS-CoV-2. Green-colored codes indicate ability to travel unrestricted in low-risk regions; yellow-colored codes indicate prohibition from major public spaces and modes of public transportation. We examined the effects of a "Health Code"-based vaccine mandate on willingness to vaccinate for COVID-19 in China.

METHODS

In August 2020, an online discrete choice experiment (DCE) was conducted among adults living in China. Participants completed up to six DCE choice sets, each containing two hypothetical COVID-19 vaccination scenario choices and a "do not vaccinate" choice. Half of the choice sets had a "Health Code" attribute that associated the "do not vaccinate" choice with a yellow Health Code implying restricted travel. Weighted, mixed effects multinomial logit regression was used to estimate preference utilities and predicted choice probabilities.

RESULTS

Overall, 873 participants completed 4317 choice sets. Most participants attained at least college-level education (90.9%). 29.8% of participants were identified as vaccine hesitators (defined as being unsure or unwilling to receive a COVID-19 vaccination). With and without the "Health Code"-based vaccine mandate, there was an 8.6% (85% CI: 6.4% - 10.92%) and 17.3% (85% CI:13.1% - 21.6%) respective predicted probability that vaccine hesitators would choose "do not vaccinate" over a common vaccination scenario currently in China (i.e., free, domestic vaccine, 80% effectiveness, 10% probability of fever side-effects, administered in a large hospital, two doses). Corresponding predicted probabilities for people who did not express vaccine hesitancy was 0.3% (93% CI: 0.0% - 14.3%) and 3.5% (93% CI:2.3% - 4.8%). The "Health Code"-based mandate significantly increased willingness to vaccinate when vaccine efficacy was greater than 60%.

CONCLUSION

Among vaccine hesitators with higher educational attainment, willingness to vaccinate for COVID-19 appears to increase if mobile technology-based vaccine mandates prohibit unvaccinated individuals from public spaces and public transportation. However, such mandates may not increase willingness if perceived vaccine efficacy is low.

Impact of the eHealth literacy, knowledge and attitudes on COVID-19 prevention behavior among residents in the second year of the COVID-19 pandemic: A cross-sectional study in Anhui Province, China

Objective

The pandemic of COVID-19 continues to challenge people's health worldwide. In the second year of the pandemic, adherence to COVID-19 preventive behavior is key to continuing efforts to overcome the epidemic. This study aims to assess the COVID-19-related knowledge, attitude, and prevention behavior (KAP) and electronic health literacy (eHealth literacy) among Anhui residents in China.

Methods

From January 30 to March 27, 2021, the cross-sectional study was performed among Anhui residents in China, including 16 cities. An online survey was adopted to assess KAP regarding COVID-19, and eHealth, involving a total of 2,122 citizens. Following informed consent, residents were recruited by convenience sampling. Frequencies and proportions were calculated. Additionally, Mann-Whitney U tests were used to analyze the variables. Independent predictors of preventive behavior of COVID-19 were ascertained using a multivariable logistic regression model.

Result

Residents demonstrated good knowledge, positive attitudes, acceptable practices, and good eHealth literacy. Online news and WeChat are the main health information resources. Citizens who had good knowledge, a positive attitude, good eHealth, and did not participate in the online lectures or training COVID-19 were more likely to take preventive measures. Those with poor health, who were male, did not have family members working in health care facilities, and did not work in a face-to-face environment were less likely to take precautions. Compared with a master's degree and above, participants with middle school education level and below took preventive behavior sometimes. Residents who browse the COVID-19 webpage <15 min weekly seldom took preventive actions.

Conclusion

The study showed that in the second year of the COVID-19 pandemic, Chinese residents had adequate knowledge of COVID-19, positive attitudes, appropriate preventive practices, and basic eHealth literacy. To prevent the rebound of the COVID-19 epidemic, the government and health agencies should inform citizens concerning which information channels or websites to use and assist the underprivileged population who lacks basic infrastructure. In addition, increasing the level of knowledge and attitude, enhancing eHealth literacy and the Health Belief Model (HBM), and implementing the Health Code were seen as ways to reinforce adherence to preventive behavior. Targeting men, implementing public awareness campaigns, community engagement strategies, and health education programs are recommended.