The Modeling of the Capacity of the Moroccan Healthcare System in the Context of COVID-19

The outbreak of SARS-Cov2 in China and its subsequent spread has caused a global pandemic. The authors conducted a simple susceptible-infected (SI) model of the spread of COVID-19 in Moroccan population. The model is based on combining the average contact rate (µmax) extracted from the early exponential phase of the outbreak with a logistic simulation over time. Interestingly, this modeling approach showed a perfect fit with a strong correlation between real confirmed and estimated cases when calibrated on the Chinese declining outbreak. Subsequently, the model was applied for studying the ongoing COVID-19 outbreak in Morocco to determine the needed time for reaching 10,000 confirmed cases whose 15% (1,500) are at risk of developing health complications requiring patient care in hospitals. The latter total capacity does not exceed 1,640 beds according to the authorities. Incorporating these parameters in the logistic model, they predicted that the Moroccan healthcare system will be at 27%, 50%, 76%, and 90% of saturation on April 11, 16, 23, and May 4, 2020, respectively.

Social mixing patterns in the UK following the relaxation of COVID-19 pandemic restrictions: a cross-sectional online survey

Background Since 23 March 2020, social distancing measures have been implemented in the UK to reduce SARS-CoV-2 transmission. We conducted a cross-sectional survey to quantify and characterize non-household contact and to identify the effect of shielding and isolating on contact patterns. Methods Through an online questionnaire, the CoCoNet study measured daily interactions and mobility of 5143 participants between 28 July and 14 August 2020. Negative binomial regression modelling identified participant characteristics associated with contact rates. Results The mean rate of non-household contacts per person was 2.9 d-1. Participants attending a workplace (adjusted incidence rate ratio (aIRR) 3.33, 95%CI 3.02 to 3.66), self-employed (aIRR 1.63, 95%CI 1.43 to 1.87) or working in healthcare (aIRR 5.10, 95%CI 4.29 to 6.10) reported significantly higher non-household contact rates than those working from home. Participants self-isolating as a precaution or following Test and Trace instructions had a lower non-household contact rate than those not self-isolating (aIRR 0.58, 95%CI 0.43 to 0.79). We found limited evidence that those shielding had reduced non-household contacts compared to non-shielders. Conclusion The daily rate of non-household interactions remains lower than pre-pandemic levels, suggesting continued adherence to social distancing guidelines. Individuals attending a workplace in-person or employed as healthcare professionals were less likely to maintain social distance and had a higher non-household contact rate, possibly increasing their infection risk. Shielding and self-isolating individuals required greater support to enable them to follow the government guidelines and reduce non-household contact and therefore their risk of infection.

Implications of the Unexpected Persistance of Human Rhinovirus/Enterovirus during the COVID-19 Pandemic in Canada

Stringent public health measures imposed across Canada to control the COVID-19 pandemic have nearly suppressed most seasonal respiratory viruses, with the notable exception of human rhinovirus/enterovirus (hRV/EV). Thanks to this unexpected persistence, we highlight that hRV/EV could serve as a sentinel for levels of contact rate in populations to inform on the efficiency¬, or the need of, public health measures to control the subsequent COVID-19 epidemic, but also for future epidemics from other seasonal or emerging respiratory pathogens.

Mathematical Modeling of Transmission Dynamics with Periodic Contact Rate and Control by Different Vaccination Rates of Hepatitis B Infection in Ghana

The paper evidenced that Hepatitis B infection is the world's deadliest liver infection and Vaccination is among the principal clinical strategies in fighting it. These have encouraged a lot of researchers to formulate mathematical models to accurately predict the mode of transmission and make deductions for better health decision-making processes. In this paper, an SEIR model is used to model the transmission of the Hepatitis B infection with periodic contact rate and examine the impact of vaccination. The model was validated using estimated data in Ghana and simulated in a MATLAB environment. The results showed that the vaccination rate has a great impact on the transmission mode of the Hepatitis B infection and the periodic contact rate may lead to a chaotic solution which could result in an uncontrolled spreading of the infection. It is concluded that even if the vaccination rate is 70%, the infection rate would reduce to the minimum barest so more newborns must be vaccinated.

Contact surveys reveal heterogeneities in age-group contributions to SARS-CoV-2 dynamics in the United States

SARS-CoV-2 is spread primarily through person-to-person contacts. Quantifying population contact rates is important for understanding the impact of physical distancing policies and for modeling COVID-19, but contact patterns have changed substantially over time due to shifting policies and behaviors. There are surprisingly few empirical estimates of age-structured contact rates in the United States both before and throughout the COVID-19 pandemic that capture these changes. Here, we use data from six waves of the Berkeley Interpersonal Contact Survey (BICS), which collected detailed contact data between March 22, 2020 and February 15, 2021 across six metropolitan designated market areas (DMA) in the United States. Contact rates were low across all six DMAs at the start of the pandemic. We find steady increases in the mean and median number of contacts across these localities over time, as well as a greater proportion of respondents reporting a high number of contacts. We also find that young adults between ages 18 and 34 reported more contacts on average compared to other age groups. The 65 and older age group consistently reported low levels of contact throughout the study period. To understand the impact of these changing contact patterns, we simulate COVID-19 dynamics in each DMA using an age-structured mechanistic model. We compare results from models that use BICS contact rate estimates versus commonly used alternative contact rate sources. We find that simulations parameterized with BICS estimates give insight into time-varying changes in relative incidence by age group that are not captured in the absence of these frequently updated estimates. We also find that simulation results based on BICS estimates closely match observed data on the age distribution of cases, and changes in these distributions over time. Together these findings highlight the role of different age groups in driving and sustaining SARS-CoV-2 transmission in the U.S. We also show the utility of repeated contact surveys in revealing heterogeneities in the epidemiology of COVID-19 across localities in the United States.

Enhancing reservoir control in the co-dynamics of HIV-VL: from mathematical modeling perspective

HIV patients are vulnerable to developing active visceral leishmaniasis (VL). To understand this complication, we studied a mathematical model for HIV and visceral leishmaniasis coinfection. In this approach, we reckoned two distinct equilibria: the disease-free and the endemic equilibria. The local and global stability of the disease-free equilibrium were thoroughly investigated. To further support the qualitative findings, we performed simulations to quantify the changes of the dynamical behavior of the full model for variation of relevant parameters. Increasing the rate of VL recovery ($\phi _{1}$ ϕ 1 ), the recovery rate for VL–HIV Co-infection ($\phi _{2}$ ϕ 2 ), removing reservoirs ($c_{1}$ c 1 ), minimizing the contact rate ($\beta _{h}$ β h ) are important in controlling the transmission of individual and co-infection disease of VL and HIV. In conclusion, possible measures should be implemented to reduce the number of infected individuals. Therefore, we recommend that policy makers and stakeholders incorporate these measures during planing and implementation phases to control the transmission of VL–HIV co-infection.

Multi-Model Selection and Analysis for COVID-19

In the face of an increasing number of COVID-19 infections, one of the most crucial and challenging problems is to pick out the most reasonable and reliable models. Based on the COVID-19 data of four typical cities/provinces in China, integer-order and fractional SIR, SEIR, SEIR-Q, SEIR-QD, and SEIR-AHQ models are systematically analyzed by the AICc, BIC, RMSE, and R means. Through extensive simulation and comprehensive comparison, we show that the fractional models perform much better than the corresponding integer-order models in representing the epidemiological information contained in the real data. It is further revealed that the inflection point plays a vital role in the prediction. Moreover, the basic reproduction numbers R0 of all models are highly dependent on the contact rate.

Strontium-Loaded Nanotubes of Ti–24Nb–4Zr–8Sn Alloys for Biomedical Implantation

Ti–24Nb–4Zr–8Sn (Ti2448) alloys, with a relatively low elastic modulus and unique mechanical properties, are desirable materials for oral implantation. In the current study, a multifaceted strontium-incorporating nanotube coating was fabricated on a Ti2448 alloy (Ti2-NTSr) through anodization and hydrothermal procedures. In vitro, the Ti2-NTSr specimens demonstrated better osteogenic properties and more favorable osteoimmunomodulatory abilities. Moreover, macrophages on Ti2-NTSr specimens could improve the recruitment and osteogenic differentiation of osteoblasts. In vivo, dense clots with highly branched, thin fibrins and small pores existed on the Ti2-NTSr implant in the early stage after surgery. Analysis of the deposition of Ca and P elements, hard tissue slices and the bone-implant contact rate (BIC%) of the Ti2-NTSr implants also showed superior osseointegration. Taken together, these results demonstrate that the Ti2-NTSr coating may maximize the clinical outcomes of Ti2448 alloys for implantation applications.

DISTRICT WISE ANALYSIS OF COVID-19 PANDEMIC TRENDS DURING SECOND WAVE IN THE STATE ANDHRA PRADESH, INDIA USING SEIR-RGS MODEL

— Andhra Pradesh is one of the south Indian states in India and having 13 districts. This is one of the most Covid-19 effected state in India during first and second waves. In India district is the major administrative block for implementing government policies and schemes under control of district collector. So, estimating or forecasting trends in district level more important than state wise or entire country wise. In this paper we are proposing Susceptible, Exposed, Infected and Recovered – Regression and Grid Search (SEIR-RGS) model for analyzing Covid -19 district wise trends during second wave. The SEIR-RGS, initially collects daily wise covid data for each district from Department of Health, medical and family welfare, AP and estimates the model parameters like contact rate, incubation rate and recovery rate. To calculate recovery rate the proposed model uses regression technique between daily active cases vs cumulative recoveries. The present model uses two phases for estimating contact rate and incubation rate using grid search approach. After that the proposed method calculates the infectious period, incubation period and basic reproduction of infection in all 13 districts to analyze trends in the state during second wave and also to predict possibility of third wave in each district.