The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19.

The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supply-constrained resource allocation strategies for controlling novel disease epidemics. To address the challenge of constrained resource optimization for managing diseases with complications like pre- and asymptomatic transmission, we develop an integro partial differential equation compartmental disease model which incorporates realistic latent, incubation, and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals. Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission. To analyze the influence of these realistic features on disease controllability, we find optimal strategies for reducing total infection sizes that allocate limited testing resources between 'clinical' testing, which targets symptomatic individuals, and 'non-clinical' testing, which targets non-symptomatic individuals. We apply our model not only to the original, delta, and omicron COVID-19 variants, but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions, which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness. We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies, while the relationship between incubation-latent mismatch, controllability, and optimal strategies is complicated. In particular, though greater degrees of presymptomatic transmission reduce disease controllability, they may increase or decrease the role of non-clinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length. Importantly, our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality.

A case series of chronic spontaneous urticaria after COVID-19 vaccination

Case report Introduction: Various immediate or delayed types of cutaneous adverse reactions such as local site reaction, urticaria, mobilliform rash, elayed large local reactions, etc. have been noted after COVID-19 vaccination, which were usually treatable with times. Here we report 13 patients with chronic spontaneous urticaria (CSU) developed after COVID-19 vaccination. Cases: Of the 13 CSU patients, four were male and mean age was 42+/-9 years (range: 28-56). Twelve patients were vaccinated with Pfizer-BioNTech COVID-19 vaccine, and one was with Oxford/ AstraZeneca vaccine. 7 patients (53.8%) were developed CSU after their first vaccination, 5 patients (38.5%) were after 2nd booster shot, and one (7.7%) were after third booster shot. Mean latent period was 7+/-6 days (range: 1-20). Mean duration of CSU were 22+/-8 weeks. Nine patients (69.2%) who refractory to 3-or 4-fold increase of H1-antihistamines took omalizumab treatment, all of whom reached well-or completely controlled status. Five of them (55.6%) achieved well-controlled status within 1 month, while 4 of them achieved well-controlled after 3 months. 1 of them took cyclosporine in addition to 300mg/4 weeks to reach well-controlled status. Conclusion(s): COVID-19 vaccination can be a cause of CSU. CSU after COVID-19 vaccination can be intractable to treatment with 4-fold increase of H1-antihistamines. Omalizumab works well to control CSU after COVID-19 vaccination.

Injection-site reactions post mRNA COVID-19 vaccination

Background: To date, over 10 million doses of mRNA vaccines (BNT162b2 mRNA and mRNA-1273) have been administered in Singapore. Initial studies have shown that 0.8% of individuals who received Moderna mRNA vaccine developed delayed injection-site reactions. Reactions to the Moderna mRNA vaccine are thought to be benign and not a contraindication to further doses. Injection-site reactions associated with the Pfizer-BioNTech mRNA vaccine are less clearly defined. We report the characteristics of mRNA COVID-19 injection-site reactions, comparing the clinical features between Moderna (mRNA-1273) and Pfizer-BioNTech (BNT162b2) reactions in the Singaporean adult population. Method(s): We retrospectively reviewed patients referred to the Dermatology Service / Allergy Centre of a tertiary hospital in Singapore for reactions post COVID-19 vaccination between 10 Jan 2021 and 26 Aug 2021. Inclusion criteria were adult patients who developed a localised injection-site reaction after either Moderna or Pfizer-BioNTech mRNA COVID-19 vaccination. Result(s): 322 patients were referred for post-COVID- 19 vaccine reactions, of which 21 developed injection-site reactions. 11 (52%) had received the Moderna mRNA vaccine while 10 (48%) received the Pfizer-BioNTech mRNA vaccine. Patients receiving the Moderna mRNA vaccine had a longer mean latency period (p = 0.047) and were more likely to have a latency duration of > 5 days (p = 0.007). Secondary dissemination of the injection-site reaction was seen in 2 patients. 11 (52%) of these reactions resolved without treatment;while the remaining 10 (48%) required symptomatic treatment with topical corticosteroids, antihistamines, or a combination of both. All 21 patients subsequently received the second vaccine dose, of which 2 (9.5%) developed recurrence of the reaction;both of which were mild and did not require treatment. Conclusion(s): Localised injection-site reactions post Moderna or Pfizer-BioNTech mRNA COVID-19 vaccination are uncommon and appear to be phenotypically different. Such reactions are benign and self-limited. While recurrence of the reaction can arise during repeat vaccine doses, these are mild and self-limited.

Clinical outcomes in vaccinated and unvaccinated patients with COVID-19: a population- based analysis

Introduction: Real-life data for vaccination against COVID-19 are sorely needed. Aim(s): This was a population based analysis aiming to investigate the risk of hospitalization for COVID-19 of 98,982 subjects and compare features of vaccinated and unvaccinated patients. Method(s): Hospitalized patients with COVID-19 between 01/07/2021 and 11/02/2022 were included in the study. Result(s): Five hundred eighty two patients (n=582) were included in the analysis [males: 58.6% (n=341), vaccinated patients: 28.5% (n=166), unvaccinated patients: 71.5% (n=416)]. Median age of vaccinated patients was significantly higher compared to median age of unvaccinated [74.0 (95% CI: 72.0 to 77.0) vs 59.0 (95% CI: 57.0 to 62.0), p=0.0001]. Mean latency time (+/-SD) from the second dose to hospitalization was 5.7 +/- 2.6 months. Between 01/07/2021 and 01/12/2021 unvaccinated subjects had higher risk for hospitalization compared to vaccinated [HR: 2.82, 95% CI: 2.30 to 3.45, p<0.0001]. Between 02/12/2021 and 11/02/2022 unvaccinated subjects presented with higher risk for hospitalization than subjects that had received booster dose [HR: 2.07, 95% CI: 1.44 to 2.98, p=0.005], but not than subjects that got two doses. Finally, age-adjusted analysis showed that hospitalized unvaccinated patients presented with significantly higher mortality risk compared to hospitalized vaccinated patients [HR: 2.59, 95% CI: 1.69 to 3.98, p<0.0001]. Conclusion(s): Vaccination against COVID-19 remains the best way to contain the pandemic. There is an amenable need for booster dose during the omicron era.

Acute Transverse Myelitis: an upcoming complication of COVID-19 infection

Objective: To assess if patients with persistent positive nasopharyngeal polymerase chain reaction (PCR) swab for SARS CoV-2 (COVID-19) virus seem to be at a higher risk of developing complications like acute transverse myelitis (ATM). Background: ATM as post-infectious sequelae was mostly attributed to bacteria-like Mycoplasma pneumonia or viruses like varicella in the pre-pandemic times. However, in the light of the world seeing two waves of the COVID-19, ATM as a post-COVID-19 sequelae is being reported more frequently. Design/Methods: The literature search was done using PubMed and Google scholar using keywords. The search criteria was set to filter cases of ATM in COVID-19 patients, reports between Jan 2020 to July 2021. A total of eight case reports were selected from peer reviewed journals. Results: The reported cases included a total of eight patients ranging from 32-72 years of age. Of the eight case reports, five presented after two weeks of initial COVID-19 symptoms. Seven of the eight patients tested positive for a nasopharyngeal PCR swab for COVID-19 at the time of presentation with ATM symptoms. The most common initial manifestation was acute onset bladder dysfunction and lower limb weakness. In six out of eight cases, magnetic resonance imaging (MRI) of the whole spine showed cervicothoracic cord hyperintensities. Treatment with intravenous methylprednisolone started on day 2 of ATM at a 1g/day dose showed clinical improvement in three patients. Intravenous immunoglobulin therapy (IVIg) at a dose of 25- 30g/day for three days showed improvement in two patients, and one patient improved with plasma exchange following steroid therapy. Conclusions: Most patients with ATM presented with a long latency period (beyond 2 weeks after the initial COVID-19 positive test) and intravenous steroid therapy helps, but most patients seem to require additional IVIg or plasma exchange before showing clinical improvement. We encourage further large scale studies in this regard.

A new SAIR model on complex networks for analysing the 2019 novel coronavirus (COVID-19).

Nowadays, the novel coronavirus (COVID-19) is spreading around the world and has attracted extremely wide public attention. From the beginning of the outbreak to now, there have been many mathematical models proposed to describe the spread of the pandemic, and most of them are established with the assumption that people contact with each other in a homogeneous pattern. However, owing to the difference of individuals in reality, social contact is usually heterogeneous, and the models on homogeneous networks cannot accurately describe the outbreak. Thus, we propose a susceptible-asymptomatic-infected-removed (SAIR) model on social networks to describe the spread of COVID-19 and analyse the outbreak based on the epidemic data of Wuhan from January 24 to March 2. Then, according to the results of the simulations, we discover that the measures that can curb the spread of COVID-19 include increasing the recovery rate and the removed rate, cutting off connections between symptomatically infected individuals and their neighbours, and cutting off connections between hub nodes and their neighbours. The feasible measures proposed in the paper are in fair agreement with the measures that the government took to suppress the outbreak. Furthermore, effective measures should be carried out immediately, otherwise the pandemic would spread more rapidly and last longer. In addition, we use the epidemic data of Wuhan from January 24 to March 2 to analyse the outbreak in the city and explain why the number of the infected rose in the early stage of the outbreak though a total lockdown was implemented. Moreover, besides the above measures, a feasible way to curb the spread of COVID-19 is to reduce the density of social networks, such as restricting mobility and decreasing in-person social contacts. This work provides a series of effective measures, which can facilitate the selection of appropriate approaches for controlling the spread of the COVID-19 pandemic to mitigate its adverse impact on people's livelihood, societies and economies.

The latent period of coronavirus disease 2019 with SARS-CoV-2 B.1.617.2 Delta variant of concern in the postvaccination era.

INTRODUCTION: Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have resulted in new challenges for epidemic prevention and control worldwide. However, little is known about the latent period of coronavirus disease by the SARS-CoV-2 Delta variant of concern (VOC) in the postvaccination era. METHODS: The epidemiology and clinical data of cases with confirmed SARS-CoV-2 Delta VOC infection were retrospective collected. Dates of the first positive PCR test were collected to estimate the distribution of latent period. RESULTS: Of the 40 patients, 16 were male (40%). The median age of patients was 47.5 years. The median latent period of patients was 6.0 days (interquartile range [IQR], 4.0-9.0 days) and the longest latent period was 13.0 days after exposure. The latent periods were longer in male patients compared to female patients (median, 8.5 days vs. 5.0 days, p = .041). The median latent period was comparable among fully vaccinated cases (6.5 days), no vaccinated cases (7.5 days), and partially vaccinated cases (5.5 days). CONCLUSIONS: The median latent period of SARS-CoV-2 Delta VOC infection was 6.0 days. The latent period between vaccinated and non-vaccinated patients was not significantly different. The 14-day quarantine program is sufficient to prevent the transmission of COVID-19 by Delta VOC in the postvaccination era.

Delayed local reactions to mRNA vaccines against COVID-19

Background: Vaccines represent an efficient means to control the pandemic of Coronavirus Disease 2019 (COVID-19). Two mRNA-based emergency vaccines have recently been licensed for mass administration: BNT162b2 and mRNA-1273 COVID-19 vaccine. Delayed hypersensitivity reactions these new vaccines can range widely from localized skin symptoms to disseminated exanthemas. Locally confined reactions can be caused by the active component or the excipients in the vaccine. Both mRNA vaccines contain polyethylene glycol (PEG) 2000 lipid conjugate as excipient. PEG and its derivatives with clinical cross-reactivity (polysorbates, laureth-9) are ubiquitous in many drugs. The mRNA-1273 COVID-19 vaccine also contains trometamol, an organic amine used extensively. Method: We reported a series of 14 patients referred to our Allergy Department with suspected delayed large local reactions (DLLR): erythematous and edematous plaques ≥10 cm in diameter accompanied by pain or pruritus, after the administration of BNT162b2 or mRNA-1273 COVID-19 vaccine between January to February 2021. We describe cutaneous manifestations,latency time, treatment and duration of the lesions. We performed patch test in the upper back with PEG 400 1% in petrolatum (pet), PEG 3350 10% pet, PEG 3350 in aqueous solution (aq), PEG 4000 10% pet, polysorbate 80 1% pet, polysorbate 80 10% pet, laureth-9/ sodium lauril sulphate 1%, trometamol 0.50% aq (only in mRNA-1273 vaccinated patients), with readings at day 2 and day 4. Results: We collected 14 patients: 13 received mRNA-1273 and only one BNT162b2 COVID-19 vaccine. Most patients (13/14) reacted to the first dose. 42.9% had detectable serum specific IgG antibodies against SARS-CoV-2 in the last 3 months. The mean size of DLLR was 11.9 ± 1.6 cm and the latency time was 4.4 ± 1.8 days. Ten patients (71.4%) not receive any treatment, and four (28.6%) received topical corticosteroids. The mean duration of the reactions was 4.75 ± 2.7 days when treated and 4.5 ± 0.60 days without treatment, with no significant differences (p = 0.79). All patients completed vaccination with the second dose and 69.2% developed DLLR again. PT were negative in the 100% cases Conclusion: We didn't found any sensitization to excipients in our 14 cases series. We thought that DLLR may occur due to a non-specific inflammatory response or represent the normal immune response to the vaccination, and in our experience, this should not be a contraindication to receive further doses of mRNA vaccines.

Systemic skin delayed reactions after the administration of BNT162b2 and mRNA-1273 COVID-19 vaccines

Background: Vaccination has become increasingly relevant to prevent the global pandemic from coronavirus disease 2019 (COVID-19). Two mRNA-based emergency vaccines have recently been licensed for mass administration: BNT162b2 and mRNA-1273 COVID-19 vaccine. Delayed vaccines hypersensitivity reactions can be caused by residual proteins, or most frequently by excipients. Both mRNA vaccines contain polyethylene glycol (PEG) 2000 lipid conjugate as excipient. PEG and its derivatives with clinical cross-reactivity (polysorbates, laureth-9) are ubiquitous in many drugs. mRNA-1273 COVID-19 vaccine also contains trometamol, an organic amine used extensively. Method: We collected the patients referred to our Allergy Department with systemic skin delayed reaction after the administration of BNT162b2 or mRNA-1273 COVID-19 vaccine between January to February 2021. We recorded age, sex, personal history of allergies and previous SARS-CoV-2 infection. We describe cutaneous manifestations, latency time, treatment, and duration. We performed patch test (PT) in the upper back with PEG 400 1% in petrolatum (pet), PEG 3350 10% pet, PEG 3350 in aqueous solution (aq), PEG 4000 10% pet, polysorbate 80 1% pet, polysorbate 80 10% pet, laureth-9/ sodium lauril sulphate 1%, trometamol 0.50% aq (only in mRNA-1273 vaccinated patients), with readings at day 2 and day 4. Results: The study population comprised 11 patients: 6 (54.5%) received BNT162b2 and the rest received mRNA-1273 COVID-19 vaccine. Most patients (10/11, 90.9%) reacted to the first dose. Almost half of them (5/11, 45.4%) had detectable serum specific IgG antibodies against SARS-CoV-2 in the last 3 months. The most frequent manifestation was generalized maculopapular exanthema (6/11, 54.5%), 2 flaking palms, 1 acute generalized exanthematous pustulosis (AGEP), 1 micropapular exanthema accompanied by a 7-centimeter blister, and 1 multiple fixed drug eruption (MFDE). PT were negative in the 100% cases. We contraindicate the second dose of the vaccine in patients with severe skin reactions (MFDE, AGEP) after the first dose (2/10, 20%). The remaining patients received the second dose, reappearing systemic skin lesions in 1/8 (12.5%), having a maculopapular exanthema again. Conclusion: In our experience, mild exanthemas should not be a contraindication to receive further doses of mRNA vaccines. However, we recommended an exhaustive allergy workout in all patients with systemic skin delayed reaction.

Epidemiology of COVID-19

On December 12, 2019, a number of cases emerged caused by an unidentified pneumonia disease outbreak in a local seafood market in Wuhan City, Hubei Province of China. Samples from five patients tested positive for coronaviruses, where 87.1% sequences were identical to the SARS-related coronaviruses. On January 8, 2020, the CSG of the ICTV named this virus SARS-CoV-2, the virus that causes COVID-19. The USA had its first COVID-19 case on January 21, 2020, in Washington State. The WHO declared COVID-19 a pandemic on March 11, 2020. Several biological and epidemiological characteristics of COVID-19 are presented: percent of asymptomatic infections, infection fatality ratio, case fatality rate, reproduction number, incubation period, latent period, and serial interval. Data are presented on the demographic overrepresentation of Blacks and Hispanics on COVID-19 deaths in 50 States and DC, as well as in 14 States with the largest Black and Hispanic populations, along with the top 5 States of residence of the Black population. Data also are offered on Blacks’ disproportional burden of COVID-19 deaths in selected counties in Florida and Georgia. It is worthy to note that, at least about 7 months into the pandemic, the USA had no strategic preparedness and response plan and persistently breached field epidemiology principles, prompting three prominent public health journals, Scientific American, The Lancet, and the New England Journal of Medicine, to deliver sweeping criticisms on the Trump Administration’s mishandling of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Threshold Dynamics of an SEIS Epidemic Model with Nonlinear Incidence Rates.

In this paper, we consider an SEIS epidemic model with infectious force in latent and infected period, which incorporates by nonlinear incidence rates. The local stability of the equilibria is discussed. By means of Lyapunov functionals and LaSalle's invariance principle, we proved the global asymptotic stability of the disease-free equilibrium and the endemic equilibrium. An application is given and numerical simulation results based on real data of COVID-19 in Morocco are performed to justify theoretical findings.

Estimating the Latent Period of Coronavirus Disease 2019 (COVID-19).

Using detailed exposure information on COVID-19 cases, we estimated the mean latent period to be 5.5 (95% CI: 5.1-5.9) days, shorter than the mean incubation period (6.9 days). Laboratory testing may allow shorter quarantines since 95% of COVID-19 cases shed virus within 10.6 (95% CI: 9.6-11.6) days of infection.

Using Proper Mean Generation Intervals in Modeling of COVID-19.

In susceptible-exposed-infectious-recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of infection attack rate (AR) and control efficacy. We argue that it is important to use suitable epidemiological parameter values for proper estimation/prediction. Furthermore, we propose an epidemic model to assess the transmission dynamics of COVID-19 for Belgium, Israel, and the United Arab Emirates (UAE). We estimated a time-varying reproductive number [R0(t)] based on the COVID-19 deaths data and we found that Belgium has the highest AR followed by Israel and the UAE.

Estimating the generation interval and inferring the latent period of COVID-19 from the contact tracing data.

The coronavirus disease 2019 (COVID-19) emerged by end of 2019, and became a serious public health threat globally in less than half a year. The generation interval and latent period, though both are of importance in understanding the features of COVID-19 transmission, are difficult to observe, and thus they can rarely be learnt from surveillance data empirically. In this study, we develop a likelihood framework to estimate the generation interval and incubation period simultaneously by using the contact tracing data of COVID-19 cases, and infer the pre-symptomatic transmission proportion and latent period thereafter. We estimate the mean of incubation period at 6.8 days (95 %CI: 6.2, 7.5) and SD at 4.1 days (95 %CI: 3.7, 4.8), and the mean of generation interval at 6.7 days (95 %CI: 5.4, 7.6) and SD at 1.8 days (95 %CI: 0.3, 3.8). The basic reproduction number is estimated ranging from 1.9 to 3.6, and there are 49.8 % (95 %CI: 33.3, 71.5) of the secondary COVID-19 infections likely due to pre-symptomatic transmission. Using the best estimates of model parameters, we further infer the mean latent period at 3.3 days (95 %CI: 0.2, 7.9). Our findings highlight the importance of both isolation for symptomatic cases, and for the pre-symptomatic and asymptomatic cases.

A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan.

In this study, an individual-based epidemic model, considering latent-infectious-recovery periods, is presented. The analytic solution of the model in the form of recursive formulae with a time-dependent transmission coefficient is derived and implanted in Excel. The simulated epidemic curves from the model fit very well with the daily reported cases of COVID-19 in Wuhan, China and New York City (NYC), USA. These simulations show that the transmission rate of NYC's COVID-19 is nearly 30% greater than the transmission rate of Wuhan's COVID-19, and that the actual number of cumulative infected people in NYC is around 9 times the reported number of cumulative COVID-19 cases in NYC. Results from this study also provide important information about latent period, infectious period and lockdown efficiency.

Dynamic analysis of a mathematical model with health care capacity for COVID-19 pandemic.

The fact that no there exists yet an absolute treatment or vaccine for COVID-19, which was declared as a pandemic by the World Health Organization (WHO) in 2020, makes very important spread out over time of the epidemic in order to burden less on hospitals and prevent collapsing of the health care system. This case is a consequence of limited resources and is valid for all countries in the world facing with this serious threat. Slowing the speed of spread will probably make that the outbreak last longer, but it will cause lower total death count. In this study, a new SEIR epidemic model formed by taking into account the impact of health care capacity has been examined and local and global stability of the model has been analyzed. In addition, the model has been also supported by some numerical simulations.

[Analysis of transmission characteristics of COVID-19 in Shaanxi Province].

A total of 245 cases of COVID-19 in Shaanxi Province reported in the China information system for disease control and prevention as of February 24, 2020 were selected as the research objects, the cases are divided into imported cases (116 cases, 47.3%) and local cases (129 cases, 52.7%), their basic characteristics, time distribution, transmission mode, intergenerational interval and latent period transmission are analyzed. The age of local cases [(51.74±15.67) years old], female patients (69 cases, 53.5%), housework and retired staff (40 cases, 31.0%), and patients isolated at the time of onset (50 cases, 38.8%) were higher than imported cases, respectively[(40.66±15.41) years old, (45 cases, 38.8%), (21 cases, 18.1%), (17 cases, 14.6%)] (P values were < 0.05); The infection rate was 0.8% (31/3 666) in close contacts with local cases, which was lower than imported cases 2.0% (69/3 435) (P<0.001); The main source of infection in local cases was relatives (70 cases, 54.3%), and the main way of infection was living together and party (90 cases, 69.8%); the proportion of latent period transmission in our province was 15.5% (20 cases), and the interval between the second-generation case and the source of infection was about 4 days, and the interval between generations was about 6 days. In summary, the main way of infection of local cases in Shaanxi Province was living together and party, there were a certain proportion of latent period transmission cases at present, it's suggested that the investigation of close contacts should be started 4 days or earlier before the onset of the case.