Disaster response: The COVID-19 pandemic and insider trading around the world

This paper investigates how corporate insiders respond to the initial COVID-19 outbreaks. Using comprehensive insider transaction data from 25 countries, we document a consistent pattern of insider selling during the month after the first COVID-19 case is confirmed in a given country. Insider selling during these disease outbreaks is less pronounced in countries with higher information disclosure requirements, higher public enforcement index, a more efficient judiciary system, and stronger investor protection. Furthermore, cultural differences and the stringency levels of government responses to the COVID-19 outbreaks help moderate insider panic selling when health disasters strike. The findings suggest that a transparent, reliable business system contributes to rebuilding investor trust and corporate resilience during crises.

Evidence of a Sjogrens disease-like phenotype following COVID-19 (preprint)

Objectives: Sjogrens Disease (SjD) is a chronic and systemic autoimmune disease characterized by lymphocytic infiltration and the development of dry eyes and dry mouth resulting from the secretory dysfunction of the exocrine glands. SARS-CoV-2 may trigger the development or progression of autoimmune diseases, as evidenced by increased autoantibodies in patients and the presentation of cardinal symptoms of SjD. The objective of the study was to determine whether SARS-CoV-2 induces the signature clinical symptoms of SjD. Methods: The ACE2-transgenic mice were infected with SARS-CoV-2. SJD profiling was conducted. COVID-19 patient sera were examined for autoantibodies. Clinical evaluations of convalescent COVID-19 subjects, including minor salivary gland (MSG) biopsies, were collected. Lastly, monoclonal antibodies generated from single B cells of patients were interrogated for ACE2/spike inhibition and nuclear antigens. Results: Mice infected with the virus showed a decreased saliva flow rate, elevated antinuclear antibodies (ANAs) with anti-SSB/La, and lymphocyte infiltration in the lacrimal and salivary glands. Sera of COVID-19 patients showed an increase in ANA, anti-SSA/Ro52, and anti-SSB/La. The male patients showed elevated levels of anti-SSA/Ro52 compared to female patients, and female patients had more diverse ANA patterns. Minor salivary gland biopsies of convalescent COVID-19 subjects showed focal lymphocytic infiltrates in four of six subjects, and 2 of 6 subjects had focus scores >2. Lastly, we found monoclonal antibodies produced in recovered patients can both block ACE2/spike interaction and recognize nuclear antigens. Conclusion: Overall, our study shows a direct association between SARS-CoV-2 and SjD. Hallmark features of SjD salivary glands were histologically indistinguishable from convalescent COVID-19 subjects. The results potentially implicate that SARS-CoV-2 could be an environmental trigger for SjD.

Ancestral origins are associated with SARS-CoV-2 susceptibility and protection in a Florida patient population (preprint)

COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. The widespread clinical symptoms encompass a large group of asymptomatic COVID-19 patients, raising a crucial question regarding genetic susceptibility, e.g., whether individual differences in immunity play a role in patient symptomatology and how much human leukocyte antigen (HLA) contributes to this. To reveal genetic determinants of susceptibility to COVID-19 severity in the population and further explore potential immune-related factors, we performed a genome-wide association study on 284 confirmed COVID-19 patients (cases) and 95 healthy individuals (controls). We compared cases and controls of European (EUR) ancestry and African American (AFR) ancestry separately. We identified two loci on chromosomes 5q32 and 11p12, which reach the significance threshold of suggestive association (p<1x10-5 threshold adjusted for multiple trait testing) and are associated with the COVID-19 susceptibility in the European ancestry (index rs17448496: odds ratio [OR] = 0.173; 95% confidence interval [CI], 0.08-0.36 for G allele; p=5.15x 10-5 and index rs768632395: OR = 0.166; 95% CI, 0.07-0.35 for A allele; p= 4.25x10-6, respectively), which were associated with two genes, PPP2R2B at 5q32, and LRRC4C at 11p12, respectively. To explore the linkage between HLA and COVID-19 severity, we applied fine-mapping analysis to dissect the HLA association with mild and severe cases. Using In-silico binding predictions to map the binding of risk/protective HLA to the viral structural proteins, we found the differential presentation of viral peptides in both ancestries. Lastly, extrapolation of the identified HLA from the cohort to the worldwide population revealed notable correlations. The study uncovers possible differences in susceptibility to COVID-19 in different ancestral origins in the genetic background, which may provide new insights into the pathogenesis and clinical treatment of the disease.

Stock market liquidity, the great lockdown and the COVID-19 global pandemic nexus in MENA countries

PurposeThe purpose of this paper is to investigate the impact of the global coronavirus (COVID-19) pandemic on stock market liquidity, while taking into account the depth and tightness dimensions.Design/methodology/approachThe author used a panel data regression on stock market dataset, representing 314 listed firms operating in six Middle East and North African (MENA) countries from February to May 2020.FindingsThe regression results on the overall sample indicate that the liquidity related to the depth measure was positively correlated with the growth in the confirmed number of cases and deaths and stringency index. Moreover, the market depth was positively related to the confirmed cases of COVID-19. The results also indicate that the liquidity of small cap and big cap firms was significantly impacted by the confirmed number of cases, while the stringency index is only significant for the liquidity depth measure. Moreover, the results regarding sectors and country level analysis confirmed that COVID-19 had a significant and negative impact of stock market liquidity.Research limitations/implicationsThis paper confirms that the global coronavirus pandemic has decreased the stock market liquidity in terms of both the depth and the tightness dimensions.Originality/valueWhile most empirical papers focused on the impact of the COVID-19 global pandemic on stock market returns, this paper investigated liquidity chock at firm level in the MENA region using both tightness and depth dimensions.

Identification of risk and protective human leukocyte antigens in COVID-19 using genotyping and structural modeling (preprint)

COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. Since innate and adaptive immune responses are elicited in COVID-19 patients, we genotyped 94 Florida patients with confirmed COVID-19 and 89 healthy controls. We identified an HLA gene, HLA-DPA1, in which specific alleles were associated with the risk of SARS-CoV-2 positivity and COVID-19 disease. HLA-DPA1*01:03 was associated with reduced incidence of SARS-CoV-2 positivity, whereas HLA-DPA1*03:01 was associated with increased risk of SARS-CoV-2 positivity. These data suggest a model in which COVID-19 severity is influenced by immunodominant peptides derived from SARS-CoV-2 preferentially presented by specific HLA-DP molecules to either protective (for asymptomatic COVID-19) or pathogenic T cells (in severe COVID-19). Although this study is limited to comparing SARS-CoV-2 positive and negative subjects, these data suggest that HLA typing of COVID-19 patients stratified for disease severity may be informative for identifying biomarkers and disease mechanisms in high-risk individuals.

Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories (preprint)

We address the problem of modeling constrained hospital resources in the midst of the COVID-19 pandemic in order to inform decision-makers of future demand and assess the societal value of possible interventions. For broad applicability, we focus on the common yet challenging scenario where patient-level data for a region of interest are not available. Instead, given daily admissions counts, we model aggregated counts of observed resource use, such as the number of patients in the general ward, in the intensive care unit, or on a ventilator. In order to explain how individual patient trajectories produce these counts, we propose an aggregate count explicit-duration hidden Markov model, nicknamed the ACED-HMM, with an interpretable, compact parameterization. We develop an Approximate Bayesian Computation approach that draws samples from the posterior distribution over the model's transition and duration parameters given aggregate counts from a specific location, thus adapting the model to a region or individual hospital site of interest. Samples from this posterior can then be used to produce future forecasts of any counts of interest. Using data from the United States and the United Kingdom, we show our mechanistic approach provides competitive probabilistic forecasts for the future even as the dynamics of the pandemic shift. Furthermore, we show how our model provides insight about recovery probabilities or length of stay distributions, and we suggest its potential to answer challenging what-if questions about the societal value of possible interventions.

Inequality and Support for Government Responses to COVID-19 (preprint)

Despite a rich literature studying the impact of inequality on policy outcomes, there has been limited effort to bring these insights into the debates about comparative support for government responses to the COVID-19 pandemic. We fill in this gap by analyzing rich survey data from six countries spanning different income levels and geographical locations—China, Italy, Japan, South Korea, the United Kingdom, and the United States—in April 2020, when most countries were facing their first surge in infections and designing their response efforts. We find that poorer individuals are less supportive of strict government responses than other groups, and that poorest individuals are least supportive. Furthermore, poorer individuals residing in more economically unequal countries are the least supportive of stringent policies. We also find that both economic and non-economic factors could affect the poor’s decisions to support stringent government policies. These findings suggest that greater transfers to the poor may ameliorate their resistance, increase support for strict policies, and may reduce the potential deepening of social inequalities caused by the pandemic, given some recent evidence that the poor and the vulnerable are most affected by the pandemic. These findings offer relevant and implementable policy advice for the ongoing global fight against the pandemic.

COVID-19 Pandemic, Government Response and Corporate Investment (preprint)

We investigate the impact of the US government response to the COVID-19 pandemic, including stringent social measures and economics support packages, on corporate investment. The empirical results show that the government response have a positive effect on corporate investment. The government response to the pandemic is not only influencing long-term investments, but also exhibits a positively significant impact on the short-term investments of the US firms. The interesting finding is that the effect of the government response on corporate investment varies cross-sectionally and is more pronounced on firms with a lower level of political risk. Further, corporate investment of firms with higher investment irreversibility react less positively to government’s policies during COVID-19. Our analyses provide fresh insights into the firms’ reaction to the government’s response to the pandemic and suggest that both social measures and economic support are vital to restoring corporate investment as well as economic recovery process.

Characterization of viral, bacterial, and parasitic causes of disease in small-scale chicken flocks in the Mekong Delta of Vietnam.

In the Mekong Delta region of Vietnam, small-scale chicken farming is common. However, high levels of disease or mortality in such flocks impair economic development and challenge the livelihoods of many rural households. We investigated 61 diseased small-scale flocks (122 chickens) for evidence of infection with 5 bacteria, 4 viruses, and helminths. Serological profiles (ELISA) were also determined against 6 of these pathogens. The aims of this study were the following: (1) to investigate the prevalence of different pathogens and to compare the probability of detection of bacterial pathogens using PCR and culture; (2) to investigate the relationship between detection of organisms in birds' tissues and the observed morbidity and mortality, as well as their antibody profile; and (3) to characterize risk factors for infection with specific viral or bacterial pathogens. We used PCR to test for viral (viruses causing infectious bronchitis [IB], highly pathogenic avian influenza [HPAI], Newcastle disease, and infectious bursal disease [IBD]) and bacterial pathogens (Mycoplasma gallisepticum, Pasteurella multocida, Avibacterium paragallinarum, and Ornithobacterium rhinotracheale [ORT]). The latter two were also investigated in respiratory tissues by conventional culture. Colisepticemic Escherichia coli was investigated by liver or spleen culture. In 49 of 61 (80.3%) flocks, at least one bacterial or viral pathogen was detected, and in 29 (47.5%) flocks, more than one pathogen was detected. A. paragallinarum was detected in 62.3% flocks, followed by M. gallisepticum (26.2%), viruses causing IBD (24.6%) and IB (21.3%), septicemic E. coli (14.8%), ORT (13.1%), and HPAI viruses (4.9%). Of all flocks, 67.2% flocks were colonized by helminths. Mortality was highest among flocks infected with HPAI (100%, interquartile range [IQR]: 81.6-100%) and lowest with flocks infected with ORT (5.3%, IQR: 1.1-9.0%). The results indicated slight agreement (kappa ≤ 0.167) between detection by PCR and culture for both A. paragallinarum and ORT, as well as between the presence of cestodes and ORT infection (kappa = 0.317). Control of A. paragallinarum, viruses causing HPAI, IBD, and IB, M. gallisepticum, and gastrointestinal helminths should be a priority in small-scale flocks.

Epidemiological Characteristics of COVID-19 Patients in Vietnam and a Description of Disease Control and Prevention Measures in Thai Binh Province (preprint)

IntroductionThe aim of this study is to describe the epidemiology of all COVID-19 patients in Vietnam and to describe the measures of disease control and prevention implemented. MethodsData were recovered from Wikipedia regarding the 2020 coronavirus pandemic in Vietnam. The period covered was from 23 January to 20 April 2020. Descriptive analysis was stratified by gender, age, country of origin, travel history, clinical symptoms and outcome. A survey of disease control and prevention measures was conducted at the Centre for Disease Control in the Thai Binh province, which is responsible for screening and isolating individuals at high risk of COVID-19. ResultsAs of 20 April 2020, Vietnam had recorded 268 confirmed COVID-19 patients. 55.2% were female. 67.9% were aged 20-49 years and 82.5% were Vietnamese. 60.4% of cases were imported from outside Vietnam. Other cases were acquired in Vietnam by individuals in close contact with imported cases. Only one patient who had not travelled had had no known contact with a confirmed case. 63.1% of patients were asymptomatic. 75.7% of patients were discharged. No deaths were recorded. The Thai Binh CDC surveyed a total of 2,203 persons at risk of COVID-19. 336 persons (15.2%) were isolated at hospitals and 1,411 (64.0%) in dedicated isolation facilities. 16.4% reported at least one respiratory symptom. No positive cases confirmed by RT-PCR have been reported in the Thai Binh province to date. ConclusionThe effect of the systematic screening and isolation strategy made it possible to limit local transmission in Vietnam. Vietnam needs to reinforce diagnostic capacities, prevention measures and provide the necessary epidemiological data on which to base interventions. The wider use of rapid serological tests is also advisable in order to be able to conduct extensive screening in the community.

Modelling the impact of control measures against the COVID-19 pandemic in Viet Nam (preprint)

Objectives: Health care system of many countries are facing a surging burden of COVID-19. Although Vietnam has successfully controlled the COVID-19 pandemic to date, there is a sign of initial community transmission. An estimate of possible scenarios to prepare health resources in the future is needed. We used modelling methods to estimate impacts of mitigation measures on the COVID-19 pandemic in Vietnam. Methods: SEIR model built in the COVIDSIM1.1 tool was adopted using available data for estimation. The herd immunization scenario was with no intervention implemented. Other scenarios consisted of isolation and social distancing at different levels (25%, 50%, 75% and 10%, 20%, 30%, respectively). Outcomes include epidemic apex, daily new and cumulative cases, deaths, hospitalized patients and ICU beds needed. Results: By April 8, 2020, there would be 465 infected cases with COVID-19 in Viet Nam, of those 50% were detected. Cumulatively, there would be 1,400 cases and 30 deaths by end of 2020, if 75% of cases was detected and isolated, and 30% of social distancing could be maintained. The most effective intervention scenario is the detection and isolation of 75% infected cases and reduction of 10% social contacts. This will require an expansion of testing capacity at health facilities and in the community, posing a challenge to identify high-risk groups to prioritized testing. Conclusions: In a localized epidemic setting, the expansion of testing should be the key measure to control the epidemic. Social distancing plays a significant role to prevent further transmission to the community.