Tropical Medicine & International Health
Objectives: In March 2020, a COVID-19 outbreak in a major referral hospital in Hanoi, Vietnam led to 7,664 patients and staff being sent into lockdown for two weeks, and more than 52,200 persons across 49 provinces being quarantined. We assessed SARS-CoV-2 transmission patterns during this to-date largest hospital outbreak in Vietnam using social network analysis (SNA). Methods: We constructed a directed relational network and calculated network metrics for ‘degree’, ‘betweenness’, ‘closeness’, and ‘eigenvector’ centrality to understand individual-level transmission patterns. We analysed network components and modularity to identify sub-network structures with disproportionately big effects. Results: We detected 68 connections between 46 confirmed cases, of whom 27 (58.7%) were ancillary support staff, seven (15.2%) caregivers, six (13%) patients, and two (4.4%) nurses. Among the ten most important cases selected by each SNA network metric, transmission dynamics clustered in 17 cases, of whom 12 (70.6%) cases were ancillary support staff. Ancillary support staff also constituted 71.1% of cases in the dominant sub-network and 68.8% of cases in the three largest sub-communities. Conclusions: We identified non-clinical ancillary support staff, who are responsible for room service and food distribution in hospital wards in Vietnam, as a group with disproportionally big impacts on transmission dynamics during this outbreak. Our findings call for a holistic approach to nosocomial outbreak prevention and response that includes both clinical and non-clinical hospital staff. Our work also shows the potential of SNA as a complementary outbreak investigation method to better understand infection patterns in hospitals and similar settings
Ha-Linh Quach, Thai Quang Pham, Ngoc Anh Hoang, Dinh Cong Phung, Viet Cuong Nguyen, Son Hong Le, Thanh Cong Le, Dang Hai Le, Anh Duc Dang, Duong Nhu Tran, Nghia Duy Ngu, Florian Vogt, Cong Khanh Nguyen
Healthcare Informatics Research
Objectives: Online misinformation has reached unprecedented levels during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed the magnitude and sentiment dynamics of misinformation and unverified information about public health interventions during a COVID-19 outbreak in Da Nang, Vietnam, between July and September 2020. Methods: We analyzed user-generated online information about five public health interventions during the Da Nang outbreak. We compared the volume, source, sentiment polarity, and engagements of online posts before, during, and after the outbreak using negative binomial and logistic regression, and assessed the content validity of the 500 most influential posts. Results: Most of the 54,528 online posts included were generated during the outbreak (n = 46,035; 84.42%) and by online newspapers (n = 32,034; 58.75%). Among the 500 most influential posts, 316 (63.20%) contained genuine information, 10 (2.00%) contained misinformation, 152 (30.40%) were non-factual opinions, and 22 (4.40%) contained unverifiable information. All misinformation posts were made during the outbreak, mostly on social media, and were predominantly negative. Higher levels of engagement were observed for information that was unverifiable (incidence relative risk [IRR] = 2.83; 95% confidence interval [CI], 1.33–0.62), posted during the outbreak (before: IRR = 0.15; 95% CI, 0.07–0.35; after: IRR = 0.46; 95% CI, 0.34-0.63), and with negative sentiment (IRR = 1.84; 95% CI, 1.23–2.75). Negatively toned posts were more likely to be misinformation (odds ratio [OR] = 9.59; 95% CI, 1.20–76.70) or unverified (OR = 5.03; 95% CI, 1.66–15.24). Conclusions: Misinformation and unverified information during the outbreak showed clustering, with social media being particularly affected. This indepth assessment demonstrates the value of analyzing online “infodemics” to inform public health responses.
Ha-Linh Quach, Thai Quang Pham, Ngoc-Anh Hoang, Dinh Cong Phung, Viet Cuong Nguyen, Son Hong Le, Thanh Cong Le, Thu Minh Thi Bui, Dang Hai Le, Anh Duc Dang, Duong Nhu Tran, Nghia Duy Ngu, Florian Vogt, Cong Khanh Nguyen
Background Trends in the public perception and awareness of COVID-19 over time are poorly understood. We conducted a longitudinal study to analyze characteristics and trends of online information during a major COVID-19 outbreak in Da Nang province, Vietnam in July-August 2020 to understand public awareness and perceptions during an epidemic. Methods We collected online information on COVID-19 incidence and mortality from online platforms in Vietnam between 1 July and 15 September, 2020, and assessed their trends over time against the epidemic curve. We explored the associations between engagement, sentiment polarity, and other characteristics of online information with different outbreak phases using Poisson regression and multinomial logistic regression analysis. We assessed the frequency of keywords over time, and conducted a semantic analysis of keywords using word segmentation Results
We found a close association between collected online information and the evolution of the
COVID-19 situation in Vietnam. Online information generated higher engagements during
compared to before the outbreak. There was a close relationship between sentiment polarity
and posts’ topics: the emotional tendencies about COVID-19 mortality were significantly
more negative, and more neutral or positive about COVID-19 incidence. Online newspaper
reported significantly more information in negative or positive sentiment than online forums
or social media. Most topics of public concern followed closely the progression of the
COVID-19 situation during the outbreak: development of the global pandemic and vaccination; the unfolding outbreak in Vietnam; and the subsiding of the outbreak after two months.
Conclusion
This study shows how online information can reflect a public health threat in real time, and
provides important insights about public awareness and perception during different outbreak
phases. Our findings can help public health decision makers in Vietnam and other low and
middle income countries with high internet penetration rates to design more effective communication strategies during critical phases of an epidemic
Asia Pacific Journal of Public Health
Ha Linh Quach, Ngoc Anh Thi Hoang, Cong Khanh Nguyen, Quang Thai Pham, Cong Dinh Phung, Nhu Duong Tran, Quynh Mai Thi Le, Duy Nghia Ngu, Anh Tu Tran, Ngoc Quang La, Dai Quang Tran, Trong Tai Nguyen, Florian Vogt, Duc Anh Dang
Travel Medicine and Infectious Disease
Ha-Linh Quach, Thai Quang Pham, Duong Nhu Tran, Mai Thi Quynh Le, Hung Thai Do, Chien Chinh Vien, Lan Trong Phan, Nghia Duy Ngu, Tu Anh Tran, Dinh Cong Phung, Quang Dai Tran, Tan Quang Dang, Duc-Anh Dang, Florian Vogt
International Journal of Infectious Diseases
Background: Vietnam implemented various public health interventions such as contact tracing and testing, mandatory quarantine, and lockdowns in response to coronavirus disease 2019 (COVID-19). However, the effects of these measures on the epidemic remain
Thai Quang Pham, Ngoc-Anh Hoang, Khanh Cong Nguyen, Samantha Colquhoun, Stephen Lambert, Luong Huy Duong, Quang Dai Tran, Duc Anh Ha, Dinh Cong Phung, Nghia Duy Ngu, Tu Anh Tran, Quang Ngoc La, Tai Trong Nguyen, Quynh Mai Thi Le, Duong Nhu Tran, Florian Vogt, Duc-Anh Dang
BMC Infectious Diseases
Background: International air travel plays an important role in the global spread of SARS-CoV-2, and tracing of close contacts is an integral part of the public health response to COVID-19. We aimed to assess the timeliness of contact tracing among airlin
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