Contact Rate Research Articles

Women in acute forensic psychiatric care: comparison of clinical, sociodemographic, and detention-related characteristics in pretrial detention, sentence execution, and court-ordered treatment

Compared to men inmates, women display decreased prevalence of severe mental disorder but increased occurrence of substance use disorders (SUD) and higher rates of previous contacts with mental health services. The group of women in detention is highly heterogeneous according to the status of incarceration (pre-trial detention (PTD), sentence execution (SE) and court ordered treatments (COT)). Studies focusing on the comparison of sociodemographic patterns, detention-related and clinical variables between these groups are still lacking. We explored these parameters in 136 women admitted for acute psychiatric care in the sole Geneva forensic unit during a nine year period (2014–2023). Sociodemographic and detention-related data included age, nationality, marital status, presence of children, education attainment, most frequently speaking language, social support, employment before conviction and type of offenses. Clinical variables included the main ICD-10 diagnosis, presence of concomitant SUD, type of personality disorders, presence of suicidal thoughts and attempts at admission, as well as number and mean duration of stays. PTD and SE women had at least 9 years of formal education in 38.9% and 30.3% of cases. Most women in PTD (77.7%), SE (56.6%) and COT (56.2%) groups were Swiss or European citizens. The level of French knowledge was excellent in most of the cases. 43.8% of COT women had at least one child and this percentage is even higher for PTD and SE cases. The employment rate before conviction was also quite high, mainly for PTD and SE (61.1% and 60.6%) and, in a lesser degree, for COT (43.8%) women. Significant social support was present in the vast majority of women without any significant group difference. The distribution of type of offenses did not differ between the three types of detention with a predominance of physical violence, and drug trafficking. The number of stays during the period of reference was significantly higher in COT compared to both SE and PTD women. History of previous inpatient care was also significantly more frequent in COT that SE and PTD women. Adjustment and affective disorders were more often found in SE and PTD cases, these diagnoses were absent in the COT group. In contrast, a main diagnosis of psychotic disorders was found in 62.5% of COT cases compared to only 21.2% in SE and 24.1% in PTD cases. The number of stays, history of inpatient care and diagnosis of psychosis were independent predictors of COT status. In conclusion, the present data reveal the good social integration and emotional support of women needing acute psychiatric care in prison independently of the type of detention. Clinically, women in PTD and SE display more often emotional distress whereas those in COT suffer from acute psychotic symptoms with previous history of psychiatric care and multiple inpatient stays.

SEIQR Model Sensitivity and Bifurcation Analysis of SARS-CoV-2 Dynamics with International in-out Mobility Control in Indonesia

This study aims to analyze the SEIQR model for the SARS-CoV-2 dynamic by considering in-out mobility. The model construction is based on the COVID-19 response strategy implemented by the Indonesian government, then analyzing the model by determining the equilibrium point and basic reproduction number, analyzing model stability, parameter sensitivity, and bifurcation. The results show that the model has stable disease-free and disease-endemic critical points when the parameter inequality conditions based on the Routh-Hurwitz criteria are satisfied. Numerical simulations show that the system takes a long time to reach equilibrium. Furthermore, the sensitivity analysis of the basic reproduction number shows that the most sensitive parameters are natural birth and death rate susceptible, contact rate of susceptible individuals with infected individuals from local and international subjects, and rate of exposed individuals who have infected. Thus, efforts to handle COVID-19 in Indonesia can be improved by focusing on controlling international in-out mobility, so that the number of exposed individuals who have been infected can be reduced. Moreover, the bifurcation analysis shows that the system undergoes forward or backward bifurcation under disease-free conditions if certain coefficient values are satisfied based on the Castillo-Chavez and Song conditions.

Contact tracing of binary stars: Pathways to stellar mergers

Stellar mergers are responsible for a wide variety of phenomena such as rejuvenated blue stragglers, highly magnetised stars, spectacular transients, iconic nebulae, and stars with peculiar surface chemical abundances and rotation rates. Before stars merge, they enter a contact phase. Here, we investigate which initial binary-star configurations lead to contact and classical common-envelope (CE) phases and assess the likelihood of a subsequent merger. To this end, we computed a grid of about 6000 detailed 1D binary evolution models with initial component masses of 0.5 − 20.0 M⊙ at solar metallicity. Both components were evolved, and rotation and tides were taken into account. We identified five mechanisms that lead to contact and mergers: runaway mass transfer, mass loss through the outer Lagrange point L2, expansion of the accretor, orbital decay because of tides, and non-conservative mass transfer. At least 40% of mass-transferring binaries with initial primary-star masses of 5 − 20 M⊙ evolve into a contact phase; > 12% and > 19% likely merge and evolve into a CE phase, respectively. Because of the non-conservative mass transfer in our models, classical CE evolution from late Case-B and Case-C binaries is only found for initial mass ratios qi < 0.15 − 0.35. For larger mass ratios, we find stable mass transfer. In early Case-B binaries, contact occurs for initial mass ratios qi < 0.15 − 0.35, while in Case-A mass transfer, this is the case for all qi in binaries with the initially closest orbits and qi < 0.35 for initially wider binaries. Our models predict that most Case-A binaries with mass ratios of q < 0.5 upon contact mainly get into contact because of runaway mass transfer and accretor expansion on a thermal timescale, with subsequent L2-overflow in more than half of the cases. Thus, these binaries likely merge quickly after establishing contact or remain in contact only for a thermal timescale. On the contrary, Case-A contact binaries with higher mass ratios form through accretor expansion on a nuclear timescale and can thus give rise to long-lived contact phases before a possible merger. Observationally, massive contact binaries are almost exclusively found with mass ratios q > 0.5, confirming our model expectations. Because of non-conservative mass transfer with mass transfer efficiencies of 15 − 65%, 5 − 25%, and 25 − 50% in Case-A, -B, and -C mass transfer, respectively (for primary-star masses above 3 M⊙), our contact, merger, and classical CE incidence rates are conservative lower limits. With more conservative mass transfer, these incidences would increase. Moreover, in most binaries, the non-accreted mass cannot be ejected, raising the question of the further evolution of such systems. The non-accreted mass may settle into circumstellar and circumbinary disks, but could also lead to further contact systems and mergers. Overall, contact binaries are a frequent and fascinating result of binary mass transfer of which the exact outcomes still remain to be understood and explored further.

Assessing the Quality of Postoperative Recovery: A Guide for Making Adjustments in Anesthesia Delivery

PurposeThe purpose of this project was to develop a plan and then implement a process for improving anesthesia delivery at a surgery center in the Southeast United States over a 2-month period. DesignThe design of the project was based on utilization of the instrument QoR-15 (Quality of recovery - 15 item questionnaire). This tool is a valid and reliable instrument for the measurement of postoperative outcomes. The QoR-15 includes 15 questions that can each be scored on a 10-point scale. MethodsMethods included a literature search, collecting pre-assessment data, making phone calls to patients utilizing QoR-15 tool, analyzing data, presenting findings to stakeholders, creating a plan of future anesthesia care adjustments. FindingsThe results revealed the following outcome data: a total of 183 postoperative phone calls were successfully performed. The calls were completed on the first postoperative day during the months of July and August 2021. There were 459 total cases during this 2-month period with 113 successful patient contacts (24.6 % successful contact rate). Mean scores of the QoR-15 data for the total population were above 9 for all 15 items. The data was then analyzed according to surgical specialty. The category of moderate pain scores in patients from the General and Ophthalmology surgical specialties were 7.9 and 7.8 respectively. General surgery patients also had one of the highest scores in severe pain with a mean of 8.7. ConclusionsIn conclusion, the leadership team at the ASC received a formal presentation of the results and recommendations for future adjustments that could be potentially implemented in anesthesia care. The benefits of regional anesthesia were suggested to help achieve better patient pain outcomes in both the General and Ophthalmologic surgical populations.

MATHEMATICAL ANALYSIS OF COVID-19 INFECTION MODEL WITH DEMOGRAPHIC DYNAMICS

This study developed a deterministic mathematical model of COVID-19 infection by incorporating asymptomatically and symptomatically infectious individuals, the vital dynamics such as birth rate and mortality rate. Face mask use, diagnosis of asymptomatic infectious individuals, and isolation of infected individuals as control strategies are also incorporated. The model is shown to have two unique equilibrium states, namely: the disease-free equilibrium points and the endemic equilibrium point. The result from the stability analysis of the critical points is shown to be local asymptotic stable and also, globally asymptotically stable provided the basic reproduction number is less than one (, and the endemic equilibrium state is local asymptotic stable and also, globally asymptotically stable provided . Furthermore, results of the sensitivity index on for the different parameters of the model show that the recruitment rate and the effective contact rate are the most sensitive parameters and thus critical in disease management and eradication. Thus, efforts geared at reducing the recruitment of susceptible individuals and infection transmission rate will significantly eliminate the disease burden.

Stochastic SIR Epidemiological Model With Two Levels of Severity

In this paper, we develop an epidemic model to analyze the spread of an infectious disease with two levels of severity within a population of varying size. Additionally, we examine the stability of the disease-free equilibrium.
 Such a model is suitable for the dynamics of COVID-19 disease spread. If the two types of infected individuals have different recovery rates, then there is no endemic equilibrium; only the disease-free equilibrium will be the subject of our study. We then study both the deterministic model and a stochastic version. The stochastic model is obtained by perturbing the contact rate using white noise. For the deterministic model, we have shown that if the basic reproduction number R_0 < 1, then the equilibrium state is globally asymptotically stable by using Lyapunov function. This implies that the disease will disappear, and the entire population will become susceptible. For the stochastic version, we demonstrate that the system admits a unique positive global solution that exists within a positively invariant domain. Under suitable conditions on the intensity of the white noise perturbations, we prove that the number of infectious individuals converge almost surely exponentially to zero and the disease-free equilibrium of system is stochastically asymptotically stable in the large provided. Finally, we give some numerical simulations to illustrate our theoretical results.

Modeling the response of an endangered rabbit population to RHDV2 and vaccination

AbstractRabbit hemorrhagic disease virus 2 (RHDV2), recently detected in the western United States, has the potential to cause mass mortality events in wild rabbit and hare populations. Currently, few management strategies exist other than vaccination. We developed a spatially explicit model of RHDV2 for a population of riparian brush rabbits (Sylvilagus bachmani riparius), a subspecies of brush rabbit classified as endangered in the United States, on a subsection of the San Joaquin River National Wildlife Refuge. The goal of our model was to provide guidance regarding vaccination strategies for an endangered rabbit species. Our model predicts that increased interactions between rabbits (a proxy for landscape connectivity) and disease transmission rates among susceptible hosts (individual brush rabbits and conspecifics) have the greatest influence on the outcome of a potential vaccination campaign. Our model projects that across a range of parameter estimates (given an RHDV2 incursion), the median estimated population size with a 0%–10% vaccination rate after 1 year is 538 rabbits (95% Confidence Interval [C.I.] 69–1235), approximately 36% of the expected size of the study population of 1470 rabbits without an RHDV2 introduction. With a 10%–20%, 20%–30%, or 30%–40% vaccination rate, the median estimated population size increased to 628 rabbits (95% C.I. 130–1298), 723 rabbits (95% C.I. 198–1317), and 774 rabbits (95% C.I. 228–1410), respectively. These estimates represent 43%, 49%, and 53% of the expected population size without an RHDV2 introduction. Overall, a 1% increase in vaccination rate was associated with a six rabbit (95% C.I. 5–7) increase in total remaining population size. This result is dependent on assumptions regarding environmental transmission, home range size (and contact rates of rabbits). Given the relatively short lifespan of rabbits and the potential need for boosters, vaccination programs are most likely to be successful for small target populations where relatively high vaccination rates can be maintained.

Electrophoretic deposition of photothermal responsive antibacterial coatings on titanium with controlled release of silver ions

Burst release of antibacterial agents generated by the surface antibacterial modification of Ti implants frequently results in a reduction in their biocompatibility and substantial toxic side effects. In this study, core-shelled nanoparticles namely AgNR@MSN, were synthesized successfully by mesoporous silica shell in-situ encapsulated Ag nanorods, and then co-deposited with chitosan to form a AgNR@MSN-chitosan composite coating on Ti substrate by electrophoretic deposition. The developed composite coating, due to the presence of AgNR, presented excellent photothermal effect under the irradiation of an 808 nm near-infrared laser, leading to both rapid increase of local temperature and triggered release of Ag ions for bacterial-killing effect against both E. coli and S. aureus. The addition of AgNR@MSN also improved the wettability of the coating and the MSN shell with mesoporous tunnels could barrier the contact and release rate of Ag to improve the biocompatibility. The developed photothermal responsive coating could be considered as a promising platform for achieving controlled release of Ag ions with outstanding antibacterial and biocompatible properties.

Switched Epidemic Models: A Contact Rate Dependent Analysis

This paper introduces a switched SQWVEAIR (Susceptible, Quarantined, Weak, Vaccinated, Exposed, Asymptomatic, Infected, and Recovered) epidemic model considering changing contact rates in an infected society. It also takes into account the presence of vulnerable individuals as frontiers in vaccination, recognizing their societal importance. The qualitative analysis of the model involves two theorems on the positive invariance set and the positivity of the solutions. Additionally, it calculates the equilibria of the proposed model and analyzes their global stabilities using the Lyapunov functional technique, focusing on the basic reproduction number (R0) as a bifurcation value. To achieve globally uniformly exponential stability, it calculates the contact-rate-dependent average dwell time (CRDADT) for each stable and unstable subsystem, developing a Lyapunov function. It also derives sufficient conditions, expressed as linear matrix inequalities (LMIs), to ensure stability. A numerical example is provided to demonstrate the effectiveness of the theoretical analysis and validate our research findings.

Functionality testing of an innovative biomechanically optimized and surface-modified orthodontic mini-screw-a comparative study.

The failure rate of orthodontic mini-screws depends strongly on primary stability and, thus, on insertion torque. Further improvement regarding the failure rate might be achieved by modifying the surface coating. Therefore, the aim of the study was to investigate the stability of anewly designed and surface-modified orthodontic mini-screw in beagle dogs. Newly designed mini-screws coated either with DOTIZE® or DOTIZE®-copper (DOT GmbH, Rostock, Germany; each: n = 24) were inserted in the mandibles of eight beagle dogs for aduration of 8months. Insertion and removal torque were measured. These data were compared to values generated by using the artificial bone material Sawbones® (Sawbones Europe AB, Malmö, Sweden). Experiments with and without torque limitation (each: n = 5) were run. The bone-to-implant contact rate and the amount of bone between the threads were examined. Statistical significance was set at P < 0.05. The success rates of the in vivo study reached high levels with 95.3% for the DOTIZE-coated and 90.5% for the DOTIZE-copper-coated screws, whereas the insertion and removal torque did not differ between the coatings. During insertion, atorque limitation of 20 Ncm was necessary to ensure that the recommended limit was not exceeded. The insertion in Sawbones without torque limitation revealed asignificantly higher torque compared to torque-limited insertion (18.2 ± 1.3 Ncm, 23.6 ± 1.3 Ncm). Bending occurred (n = 5) in the thread-free part of the mini-screw. Surface coating might be able to improve the performance of orthodontic mini-screws. The study showed high success rates and stable mini-screws until the end of observation. Further investigations are necessary.

An Application of the Caputo Fractional Domain in the Analysis of a COVID-19 Mathematical Model

Vaccination programs aimed at preventing the spread of the coronavirus appear to have a significant global impact. In this research, we have investigated a mathematical model projecting COVID-19 disease spread by considering five groups of individuals viz. vulnerable, exposed, infected, unreported, recovered, and vaccinated. Looking at the current abnormal pattern of the virus spread in the projected model, we have implemented the fractional derivative in the Mittag-Leffler context. Using the existing theory of the fractional derivative, we have examined the theoretical aspects such as the existence and uniqueness of the solutions, the existence and stability of the disease-free and endemic equilibrium points, and the global stability of the disease-free equilibrium point. In computing the basic reproduction number, we have analyzed that the existence and stability of points of equilibrium are dependent on this number. The sensitivity of the basic reproduction number is also examined. The importance of the vaccination drive is highlighted by relating it to the basic reproduction number. Finally, we have presented the simulation of the numerical results by capturing the profile of each group under the influence of the fractional derivative and investigated the impact of vaccination rate and contact rate in controlling the disease by applying the Adams-Bashforth-Moultan (ABM) method. The present research study demonstrates the importance of the vaccination campaign and the curb on individual contact by featuring a novel fractional operator in the projected model and capturing the corresponding consequence.

Fractional commensurate model on COVID‐19 with microbial co‐infection: An optimal control analysis

AbstractCrossover behaviors have always existed in the history of infectious pandemics due to a few distinct, erratic spread outlines. This research aims to investigate the crossover behavior of the proposed SVICR commensurate fractional model for the COVID‐19 delta variant, considering microbial coinfections. A mathematical model in terms of Atangana–Baleanu Caputo (ABC) category fractional integrals takes into account the co‐infection of mucormycosis in immunocompromised COVID‐19 patients caused by microbial infections. ABC operators preserve the intact history of the happenings under contemplation through its nonsingular kernel. It is observed that the framed five‐compartmental SVICR model is positively bounded on R5, the solution space. Two equilibrium points representing the survival and annihilation of sickness respectively are contributed by the single population N(t), which is counted in five dependent compartments: The bilinear growth rate of new additional infections from the contagious infectives over time ‘t’ is viewed through the threshold metric Lyapunov's stability function examines the parametric influences over the virulent spread globally. The significant focus is to investigate the Mucormycosis cases in COVID‐19 patients with underlying diabetic complications. Diabetes mellitus is the major concern for several coinfections among COVID‐19 recoveries. Aiming to minimalize the critical states, an Lagrangian–Hamiltonian optimum control structure is also performed for the SVICR model by introducing control variables in effect to tri‐control probes of minimized contact rates, persuasive vaccinations, and glycemic control of post recovered diabetic patients. The hike in the Severity of the ailment due to fungal pathogens is studied through numerical convergence of predictor–corrector scheme and simulations. Using estimated parametric values from the statistical data of mucormycosis and infections of COVID‐19 reported cases in India, the prominence of control effects are visualized graphically. To conclude, a complete qualitative analysis of the minimization problem is executed for different levels of control values. We avow that effective control intrusions would almost certainly decline the complexities associated with the viral pathogens.

A meta-analysis of voter mobilization tactics by electoral salience

After hundreds of field experiments assessing their effectiveness, voter mobilization tactics are often considered “settled science.” In this research note, we posit that this assumption is incorrect, due to inconsistent and insufficient attention to electoral salience in the literature. Researchers often conduct mobilization field experiments in low-salience elections due to limited resources and the need for adequate statistical power. However, practitioners often apply these findings in high-salience contexts. Theory suggests that effects of mobilization tactics will attenuate in high-salience elections due to heightened attention. We present refined meta-analytic estimates of common mobilization tactics in U.S. elections—canvassing, phone calls, direct mail, and SMS messages—based on electoral salience. Results show that effects of tactics attenuate 33%–76% from low- to high-salience contexts. We translate all findings into intent-to-treat (ITT) estimates to highlight the impact of declining contact rates. Finally, we identify significant gaps in the research and offer solutions.

Final epidemic size and critical times for susceptible-infectious-recovered models with a generalized contact rate.

During the spread of an infectious disease, the contact rate or the incidence rate may affect disease characteristics. For simplicity, most disease models assume standard incidence or mass action rates to calculate the basic reproduction number, final epidemic size, and peak time of an epidemic. For standard incidence, the contact rate remains constant resulting in the incidence rate is inversely proportional to the population size, while for the mass action rate, this contact rate is proportional to the total population size resulting in the incidence rate is independent of the population size. In this paper, we consider susceptible-infectious-recovered epidemic models with a generalized contact rate C(N) and a nonlinear incidence rate in view of the behavioral change from susceptible or infectious individuals when an infectious disease appears. The basic reproduction number and the final size equation are derived. The impact of different types of contact rates on them is studied. Moreover, two critical times (peak time and epidemic duration) of an epidemic are considered. Explicit formulas for the peak time and epidemic duration are obtained. These formulas are helpful not only for taking early effective epidemic precautions but also for understanding how the epidemic duration can be changed by acting on the model parameters, especially when the epidemic model is used to make public health policy.

Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model.

Mpox (formerly monkeypox) is an infectious disease that spreads mostly through direct contact with infected animals or people's blood, bodily fluids, or cutaneous or mucosal lesions. In light of the global outbreak that occurred in 2022-2023, in this paper, we analyzed global Mpox univariate time series data and provided a comprehensive analysis of disease outbreaks across the world, including the USA with Brazil and three continents: North America, South America, and Europe. The novelty of this study is that it delved into the Mpox time series data by implementing the data-driven methods and a mathematical model concurrently-an aspect not typically addressed in the existing literature. The study is also important because implementing these models concurrently improved our predictions' reliability for infectious diseases. We proposed a traditional compartmental model and also implemented deep learning models (1D- convolutional neural network (CNN), long-short term memory (LSTM), bidirectional LSTM (BiLSTM), hybrid CNN-LSTM, and CNN-BiLSTM) as well as statistical time series models: autoregressive integrated moving average (ARIMA) and exponential smoothing on the Mpox data. We also employed the least squares method fitting to estimate the essential epidemiological parameters in the proposed deterministic model. The primary finding of the deterministic model is that vaccination rates can flatten the curve of infected dynamics and influence the basic reproduction number. Through the numerical simulations, we determined that increased vaccination among the susceptible human population is crucial to control disease transmission. Moreover, in case of an outbreak, our model showed the potential for epidemic control by adjusting the key epidemiological parameters, namely the baseline contact rate and the proportion of contacts within the human population. Next, we analyzed data-driven models that contribute to a comprehensive understanding of disease dynamics in different locations. Additionally, we trained models to provide short-term (eight-week) predictions across various geographical locations, and all eight models produced reliable results. This study utilized a comprehensive framework to investigate univariate time series data to understand the dynamics of Mpox transmission. The prediction showed that Mpox is in its die-out situation as of July 29, 2023. Moreover, the deterministic model showed the importance of the Mpox vaccination in mitigating the Mpox transmission and highlighted the significance of effectively adjusting key epidemiological parameters during outbreaks, particularly the contact rate in high-risk groups.

Analysis of HIV/AIDS Model with Nonlinear Incidence Function

Human Immunodeficiency Virus – Acquired Immune Deficiency Syndrome HIV/AIDS stands as one of the most prevalent sexually transmitted disease globally and is regarded as one of the deadliest epidemic in human history. This study presents a mathematical model for understanding the dynamics of HIV/AIDS transmission, incorporating a saturated incidence rate. The model employs a system of ordinary differential equations, comprising various group of individuals including susceptible, asymptomatic infective, symptomatic infective, treated and AIDS class. The validity of the solution states affirms that the model is well-defined and holds epidemiological significance. The disease-free and endemic equilibrium states are identified, and their stability is analyzed using Routh Hurwitz criteria. Sensitivity analysis was carried out using normalized forward sensitivity index and result showed that the contact rate is the most sensitive parameter. However, it is observed from the numerical simulation that screening and treatment of the infective play a significant role in reducing the transmission of the disease. The outcome of the stability analysis for both disease-free and endemics equilibrium states indicates the potential for HIV/AIDS control.

Modeling the impact of distancing measures on infectious disease spread: a case study of COVID-19 in the Moroccan population.

This paper explores the impact of various distancing measures on the spread of infectious diseases, focusing on the spread of COVID-19 in the Moroccan population as a case study. Contact matrices, generated through a social force model, capture population interactions within distinct activity locations and age groups. These matrices, tailored for each distancing scenario, have been incorporated into an SEIR model. The study models the region as a network of interconnected activity locations, enabling flexible analysis of the effects of different distancing measures within social contexts and between age groups. Additionally, the method assesses the influence of measures targeting potential superspreaders (i.e., agents with a very high contact rate) and explores the impact of inter-activity location flows, providing insights beyond scalar contact rates or survey-based contact matrices. The results suggest that implementing intra-activity location distancing measures significantly reduces in the number of infected individuals relative to the act of imposing restrictions on individuals with a high contact rate in each activity location. The combination of both measures proves more advantageous. On a regional scale, characterized as a network of interconnected activity locations, restrictions on the movement of individuals with high contact rates was found to result in a $ 2 \% $ reduction, while intra-activity location-based distancing measures was found to achieve a $ 44 \% $ reduction. The combination of these two measures yielded a $ 48\% $ reduction.

Possible counter-intuitive impact of local vaccine mandates for vaccine-preventable infectious diseases.

We modeled the impact of local vaccine mandates on the spread of vaccine-preventable infectious diseases, which in the absence of vaccines will mainly affect children. Examples of such diseases are measles, rubella, mumps, and pertussis. To model the spread of the pathogen, we used a stochastic SIR (susceptible, infectious, recovered) model with two levels of mixing in a closed population, often referred to as the household model. In this model, individuals make local contacts within a specific small subgroup of the population (e.g., within a household or a school class), while they also make global contacts with random people in the population at a much lower rate than the rate of local contacts. We considered what would happen if schools were given freedom to impose vaccine mandates on all of their pupils, except for the pupils that were exempt from vaccination because of medical reasons. We investigated first how such a mandate affected the probability of an outbreak of a disease. Furthermore, we focused on the probability that a pupil that was medically exempt from vaccination, would get infected during an outbreak. We showed that if the population vaccine coverage was close to the herd-immunity level, then both probabilities may increase if local vaccine mandates were implemented. This was caused by unvaccinated pupils possibly being moved to schools without mandates.

Effectiveness of contact tracing for COVID-19 in Belgium

Contact tracing and investigation can prevent infectious disease transmission when carried out promptly. Data obtained from contact tracing also provides unique information on transmission dynamics that can be useful for policy making. The proportion of secondary infections arising from index cases that were previously identified as a close contact, hence “known index cases”, has been indicated by ECDC as a key performance indicator for contact tracing. Few empirical studies have been published on the effectiveness of contact tracing and investigation during the COVID-19 pandemic.&#x0D; Using data from the Belgian COVID-19 contact tracing (Sept 2020 – Dec 2021), we investigated the impact of contact tracing on onward transmission. Known index cases were compared to those not previously identified as close contact. More specifically, we compared their traced contacts and secondary cases as well as the serial interval, representing the time from illness onset in the primary case to illness onset in the secondary case. In addition, we investigated contact and transmission characteristics by age.&#x0D; Known index cases, previously informed about their exposure, were linked to fewer high-risk contacts and secondary infections. In addition, they presented a lower secondary attack rate compared to those not previously identified by contact investigation, suggesting behavioural changes. Also, a shorter serial interval was observed for known index cases. In addition to breaking transmission chains, contact tracing provides important information on transmission characteristics. When exploring age-specific data, we observed increased transmission rates from children to adults during the circulation of Delta and Omicron variants without an increase in contact rates between these age groups.&#x0D; The lower secondary attack rates for known index cases suggest that contact tracing in Belgium has been effective in reducing onward transmission. Their lower number of traced contacts and shorter serial interval are indicative that individuals aware of their exposure to SARS-CoV-2 were more reserved in their social contact behaviour. This reflects the mandatory quarantine for high-risk contacts. Our study also shows that in times of high burden on the healthcare system, key performance indicators of contact tracing should be interpreted with caution in light of changing intervention strategies. Many external factors influence the effectiveness of contact tracing like testing policy and compliance, the cooperation of index cases, and the imposed and adopted quarantine and isolation policies.&#x0D;

Stochastic Model of Pneumonia and Meningitis Co-infection Using Continuous Time Markov Chain Approach

Pneumonia disease is a lung infection caused by Streptococcus pneumoniae. Meningitis is an infection of the meninges and cerebrospinal fluid caused by Streptococcus pneumoniae. Both diseases may occur at the same time. A mathematical model is needed to represent the spread of pneumonia and meningitis co-infection. This study aims to build the stochastic model of pneumonia and meningitis co-infection with CTMC, determine the transition and outbreak probability, and conduct simulations to assess the effect of increasing the contact rate on pneumonia and meningitis . Based on the computer simulation undertaken, it can be concluded that if was decreased while was set to be fixed, the probability of disease outbreak decreased. If was set to be fixed while was decreased, the probability of disease outbreak decreased. However, the latter is smaller than the previous. Similarly, if was increased while was set to be fixed, the probability of disease outbreak increased. If was set to be fixed while was increased, the probability of disease outbreak increased. However, the latter is smaller than the previous. Moreover, if both and were decreased, the probability of disease outbreak was equal to zero.