Unraveling varying spatiotemporal patterns of dengue and associated exposure-response relationships with environmental variables in Southeast Asian countries before and during COVID-19 (preprint)

The enforcement of COVID-19 interventions by diverse governmental bodies, coupled with the indirect impact of COVID-19 on short-term environmental changes (e.g. plant shutdowns lead to lower greenhouse gas emissions), influences the dengue vector. This provides a unique opportunity to investigate the impact of COVID-19 on dengue transmission and generate insights to guide more targeted prevention measures. We aim to compare dengue transmission patterns and the exposure-response relationship of environmental variables and dengue incidence in the pre- and during-COVID-19 to identify variations and assess the impact of COVID-19 on dengue transmission. We initially visualized the overall trend of dengue transmission from 2012-2022, then conducted two quantitative analyses to compare dengue transmission pre-COVID-19 (2017-2019) and during-COVID-19 (2020-2022). These analyses included time series analysis to assess dengue seasonality, and a Distributed Lag Non-linear Model (DLNM) to quantify the exposure-response relationship between environmental variables and dengue incidence. We observed that all subregions in Thailand exhibited remarkable synchrony with a similar annual trend except 2021. Cyclic and seasonal patterns of dengue remained consistent pre- and during-COVID-19. Monthly dengue incidence in three countries varied significantly. Singapore witnessed a notable surge during-COVID-19, particularly from May to August, with cases multiplying several times compared to pre-COVID-19, while seasonality of Malaysia weakened. Exposure-response relationships of dengue and environmental variables show varying degrees of change, notably in Northern Thailand, where the peak relative risk for the maximum temperature-dengue relationship rose from about 3 to 17, and the max RR of overall cumulative association 0-3 months of relative humidity increased from around 5 to 55. Our study is the first to compare dengue transmission patterns and their relationship with environmental variables before and during COVID-19, showing that COVID-19 has affected dengue transmission at both the national and regional level, and has altered the exposure-response relationship between dengue and the environment.

Childhood Handwashing Habit Formation and Later COVID-19 Preventive Practices: A Cohort Study.

OBJECTIVE: This study identified developmental patterns of handwashing habit formation during childhood and examined their associations with later COVID-19 preventive practices. METHODS: We used data from the Taiwan Birth Cohort Study, which included 11,254 adolescents with complete data on childhood handwashing behavior and age-15 COVID-19 survey items. Bias-adjusted 3-step latent class analysis was used to test study hypotheses. RESULTS: The rates of handwashing and mask-wearing during the pandemic were 63.8% and 93.8%, respectively. Five distinct patterns of handwashing habit formation were identified: early formation (14.89%), delayed formation (17.73%), gradual formation (42.98%), inconsistent formation (9.78%), and nonformation (14.62%). Compared with adolescents with an early formation pattern of handwashing habits, those with other patterns exhibited lower odds ratios (ORs) of handwashing during COVID-19; these ORs were 0.67 (95% confidence interval [CI], 0.49-0.85), 0.60 (95% CI, 0.44-0.77), 0.29 (95% CI, 0.08-0.49), and 0.21 (95% CI, 0.01-0.40) for those with delayed formation, gradual formation, inconsistent formation, and nonformation patterns, respectively. Moreover, relative to that of adolescents with the early formation pattern, mask-wearing was less common among adolescents with gradual formation, inconsistent formation, and nonformation patterns, with ORs of 0.54 (95% CI, 0.16-0.92), 0.50 (95% CI, 0.03-0.96), and 0.26 (95% CI, 0.00-0.65), respectively. CONCLUSIONS: The early formation of hygienic habits is associated with higher adherence to pandemic preventive practices among adolescents. Our findings suggest that interventions to promote hygienic behaviors can start as early as age 3 through the introduction of healthy habits such as handwashing.

Impact of initial outbreak locations on transmission risk of infectious diseases in an intra-urban area (preprint)

Infectious diseases usually originate from a specific location within a city. Due to the heterogenous distribution of population and public facilities, and the structural heterogeneity of human mobility network embedded in space, infectious diseases break out at different locations would cause different transmission risk and control difficulty. This study aims to investigate the impact of initial outbreak locations on the risk of spatiotemporal transmission and reveal the driving force behind high-risk outbreak locations. First, integrating mobile phone location data, we built a SLIR (susceptible-latent-infectious-removed)-based meta-population model to simulate the spreading process of an infectious disease (i.e., COVID-19) across fine-grained intra-urban regions (i.e., 649 communities of Shenzhen City, China). Based on the simulation model, we evaluated the transmission risk caused by different initial outbreak locations by proposing three indexes including the number of infected cases (CaseNum), the number of affected regions (RegionNum), and the spatial diffusion range (SpatialRange). Finally, we investigated the contribution of different influential factors to the transmission risk via machine learning models. Results indicates that different initial outbreak locations would cause similar CaseNum but different RegionNum and SpatialRange. To avoid the epidemic spread quickly to more regions, it is necessary to prevent epidemic breaking out in locations with high population-mobility flow density. While to avoid epidemic spread to larger spatial range, remote regions with long daily trip distance of residents need attention. Those findings can help understand the transmission risk and driving force of initial outbreak locations within cities and make precise prevention and control strategies in advance.

Optimize Data-Driven Multi-Agent Simulation for COVID-19 Transmission (preprint)

Background: Multi-Agent Simulation is an essential technique for exploring complex systems. In researches of contagious diseases, it is widely exploited to analyze their spread mechanisms, especially for preventing COVID-19. Nowadays, transmission dynamics and interventions of COVID-19 have been elaborately established by this method, but its computation performance is seldomly concerned. As it usually suffers from inadequate CPU utilization and pour data locality, optimizing the performance is challenging. Results: This paper explores approaches to optimize multi-agent simulation for COVID-19 disease. The focus of this work is on the algorithm and data structure designs for improving performance, as well as its parallelisation strategies. We propose two successive methods to optimize the computation. We construct a case-focused iteration algorithm to improve data locality, and create a thread-safe data-mapping paradigm called hierachical hash table to accelerate hash operations. Conclusions: Our performance results demonstrate capabilities of these methods exhibiting significant improvements of system performance. The case-focused method degrades $\sim 90 \%$ cache references and achieves $\times 4.3$ speedup. Hierachical hash table can further boost computation speed by 47\%. And parallel implementation with 20 threads on CPU achieves $\times 81$ speedup consequently.

Clinical application of and nursing practices for convalescent plasma transfusion in patients with COVID-19 (preprint)

Background: This study aimed to examine the effect of convalescent plasma transfusion on patient with severe coronavirus disease ( COVID-19 ) and discussed the main nursing practices. Methods: We retrospectively analyzed the clinical data of 21 patients with severe COVID-19 who had received convalescent plasma transfusion therapy between March 1 and April 1, 2020. The observation indicators included leukocyte, lymphocyte, C-reactive protein (CRP), interleukin-6 (IL-6), and viral antibody levels; test results from pharyngeal swabs; nucleic acid test results; chest CT results; and respiratory symptoms. Further, we summarized the nursing practices related to plasma transfusion. Results: Neither death nor transfusion-related adverse reactions were observed in patients treated with convalescent plasma transfusion. Their antibody levels, especially IgG (P < 0.05), were increased to different levels, whereas the levels of inflammatory markers (CRP), white blood cells, and lymphocytes were significantly decreased (P < 0.05). Respiratory symptoms showed an improvement, and chest CT showed stable findings. Conclusions: Convalescent plasma transfusion is safe and feasible. It can increase antibody levels, reduce inflammatory factor levels, improve white blood cell and lymphocyte counts, and improve respiratory symptoms in patients with severe COVID-19. Thus, plasma transfusion can be used as a new, effective COVID-19 treatment method that requires cooperation from nursing.

Molecular basis for kinin selectivity and activation of the human bradykinin receptors (preprint)

Bradykinin and kallidin are endogenous kinin peptide hormones that belong to the kallikrein-kinin system and are essential to the regulation of blood pressure, inflammation, coagulation, and pain control. Des-Arg 10 -kallidin, the carboxy-terminal des-Arg metabolite of kallidin, and bradykinin selectively activate two G protein-coupled receptors, type 1 and type 2 bradykinin receptors (B1R and B2R), respectively. The hyperactivation of bradykinin receptors, termed “bradykinin storm”, is associated with pulmonary edema in COVID-19 patients, suggesting that bradykinin receptors are important targets for COVID-19 intervention. Here we report two G protein complex structures of B1R and B2R bound to des-Arg 10 -kallidin and bradykinin. Combined with functional analysis, our structures reveal the mechanism of ligand selectivity and specific activation of the bradykinin receptor. These findings also provide a framework for guiding drug design targeting bradykinin receptors for the treatment of inflammation, cardiovascular disorders, and COVID-19.

Effectiveness of Contact Tracing, Mask Wearing and Prompt Testing on Suppressing COVID-19 Resurgences in Megacities: An Individual-Based Modelling Study (preprint)

Background: Secondary waves of COVID-19 loom in many countries as strict physical distancing measures have been lifted. Since megacities have been hardest hit by the disease, science-based guidelines of non-pharmaceutical interventions are still in need for post-epidemic management in ‘business as usual’ cities before vaccines are widely available. This study aims to investigate the combined effects of contact tracing, mask wearing, and prompt testing on minimizing the risk of next COVID-19 waves in megacities. Methods: We integrated 5·8 million mobile phone users’ trajectory records into a spatially explicit individual-based model for simulating COVID-19 spread among 4·5 million households, 230 thousand workplaces (including schools), and other public places in 0.6 million buildings in Shenzhen city, China, which has been gradually reopened. Government interventions were incorporated to reconstruct the actual course of the 1st wave epidemic. After validated by empirical data, the model was used to assess the probability of resurgences if sporadic cases occurred in a fully reopened city under different scenarios of contact tracing settings (household, work, school, and public place), mask use, and test-seeking behavior along with receding public vigilance. Findings: Our model well predicted the spatiotemporal dynamics of the 1st wave epidemic in Shenzhen, by age distribution of symptomatic cases, and household secondary attack rate (11·02%). After city reopens, our results show a 50% chance or less of suppressing disease resurgence if not implementing contact tracing. Tracing household contacts, in combination with mandatory (100% compliance) mask use and prompt testing could limit the probability of next outbreak under 5%. If contact tracing can be expanded to work/class group members, the public compliance of masking and testing can be relaxed to 80% and 40%, respectively, to achieve the same suppression target. Further scaled-up contact tracing that includes casual contacts can suppress resurgences with a low compliance to mask use (40%) and prompt testing (20%-40%). Interpretation: To minimize the risk of resurgence in a reopened city, the local government is expected to spare no efforts to trace close contacts in household, workplace and school for a confirmed case. The authorities should promote mask use in a public space and encourage people with COVID-19-like symptoms to testing within two days after illness onset, along with measures such as sick leave compensation and extensive temperature screening in public places.Funding Statement: National Scientific Foundation of China, R & D project of key areas in Guangdong Province, Bill & Melinda Gates Foundation, Joint Engineering Research Center for Health Big Data Intelligent Analysis TechnologyDeclaration of Interests: We declare no competing interests.

Effectiveness of Contact Tracing, Mask Wearing and Prompt Testing on Suppressing COVID-19 Resurgences in Megacities: An Individual-Based Modelling Study (preprint)

Background: As COVID-19 resurges in many countries, science-based guidelines of non-pharmaceutical interventions are still in need for post-epidemic management in ‘business as usual’ cities before vaccines are widely available. This study aims to investigate the combined effects of contact tracing, mask wearing, and prompt testing on minimizing the risk of next COVID-19 waves caused by sporadic outbreaks in megacities.Methods: We integrated large-scale mobile phone tracking data into a spatially explicit individual-based model to simulate COVID-19 spread among 11.2 million individuals in Shenzhen City, China. Government interventions were incorporated to reconstruct the actual course of the 1st wave epidemic. After validated by empirical data, the model was used to assess the probability of resurgences if sporadic cases occurred in a fully reopened city under different scenarios of contact tracing settings (household, work, school, and public place), mask use, and test-seeking behavior along with receding public vigilance.Results: Our model well predicted the spatiotemporal dynamics of the 1st wave epidemic in Shenzhen, by age distribution of symptomatic cases, and household secondary attack rate (11·02%). After city reopens, our results show a 50% chance or less of suppressing disease resurgence if not implementing contact tracing. Tracing household contacts, in combination with mandatory (100% compliance) mask use and prompt testing could limit the probability of next outbreak under 5%. If contact tracing can be expanded to work/class group members, the public compliance of masking and testing can be relaxed to 80% and 40%, respectively, to achieve the same suppression target. Further scaled-up contact tracing that includes casual contacts can suppress resurgences with a low compliance to mask use (40%) and prompt testing (20%-40%). Conclusions: To minimize the risk of resurgence in a reopened city, the local government is expected to spare no efforts to trace close contacts in household, workplace and school for a confirmed case. The authorities should promote mask use in a public space and encourage people with COVID-19-like symptoms to testing within two days after illness onset, along with measures such as sick leave compensation and extensive temperature screening in public places.

Knowledge, attitudes and practices of the Chinese public with respect to coronavirus disease (COVID-19): An online cross-sectional survey (preprint)

Background: Coronavirus disease (COVID-19) has become a pandemic. The knowledge, attitudes, and practices (KAP) of the public play a major role in the prevention and control of infectious diseases. The objective of the present study was to evaluate the KAP of the Chinese public and to assess potential influencing factors related to practices. Methods: : A cross-sectional online survey was conducted in China in February 2020 via a self-designed questionnaire comprising 33 questions assessing KAP. Results: : For the 2,136 respondents from 30 provinces or municipalities in China, the accurate response rate for the knowledge section ranged from 72.7% to 99.5%, and the average was 91.2%. Regarding attitude section, the percentage of positive attitudes (“strongly agree” and “agree”) ranged from 94.7% to 99.7%, and the average value was 98.0%. The good practices (“always” and “often”) results ranged from 76.1% to 99.5%, and the average value was 96.8%. The independent samples t-test revealed that gender and ethnic differences had no effect on knowledge, attitude or behaviour (P>0.05). However, knowledge was associated with age (t=4.842, p<0.001), marital status (t=-5.323, p<0.001), education level (t=8.441, p<0.001), occupation (t=-10.858, p<0.001), and place of residence (t=7.929, p<0.001). Similarly, attitude was associated with marital status (t=-2.383, p=0.017), education level (t=2.106, p=0.035), occupation (t=-4.834, p<0.001), and place of residence (t=4.242, p<0.001). The multiple linear regression analysis results showed that the factors influencing practices were knowledge (t=-3.281, p=0.001), attitude (t=18.756, p<0.001), occupation (t=-3.860, p<0.001), education level (t=3.136, p=0.002), and place of residence (t=3.257, p=0.001). Conclusions: : The Chinese public exhibited a good level of knowledge of COVID-19, a positive attitude, and high adherence to good practices. COVID-19-related knowledge, attitudes and practices were affected by age, marital status, education level, occupation, and place of residence to varying degrees. In addition, practices were affected by knowledge and attitudes towards COVID-19.

COVID-19 Treatment: Close to a Cure? – A Rapid Review of Pharmacotherapies for the Novel Coronavirus (preprint)

Currently, there is no specific treatment for COVID-19 proven by clinical trials. WHO and CDC guidelines therefore endorse supportive care only. However, frontline clinicians have been applying several virus-based and host-based therapeutics in order to combat SARS-CoV-2. Medications from COVID-19 case reports, observational studies and the COVID-19 Treatment Guideline issued by the China's National Health Commission (7th edition published March 3rd, 2020. Edited translation attached) are evaluated in this review. Key evidence from relevant in vitro researches, animal models and clinical studies in SARS-CoV-2, SARS-CoV and MERS-CoV are examined. Antiviral therapies remdesivir, lopinavir/ritonavir and umifenovir, if considered, could be initiated before the peak of viral replication for optimal outcomes. Ribavirin may be beneficial as an add-on therapy and is ineffective as a monotherapy. Corticosteroids use should be limited without indicating comorbidities. IVIG is not recommended due to lack of data in COVID-19. Xuebijing may benefit patients with complications of bacterial pneumonia or sepsis. The efficacy of interferon is unclear due to conflicting outcomes in SARS and MERS studies. Chloroquine and hydroxychloroquine have shown in vitro inhibition of SARS-CoV-2 and may be beneficial as both prophylactic and treatment therapy. For patients who developed cytokine release syndrome, interleukin-6 inhibitors may be beneficial. Given the rapid disease spread and increasing mortality, active treatment with readily available medications may be considered timely prior to disease progression.

A mathematical model for simulating the transmission of Wuhan novel Coronavirus (preprint)

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probable be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from a seafood market (reservoir) to people, we simplified the model as Reservoir-People transmission network model. The basic reproduction number (R0) was calculated from the RP model to assess the transmissibility of the 2019-nCoV.