Analysis of Intervention Effectiveness Using Early Outbreak Transmission Dynamics to Guide Future Pandemic Management and Decision-Making in Kuwait

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the basic reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well.

Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts

The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the R0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible R0 for the 152 countries and chose one country from each quarter as a representative for four social contact categories (Canada, China, Mexico, and Niger). The model was then used to predict the effects of lockdown timing in those four categories through the representative countries. The analysis for the effect of a lockdown was performed without the influence of the other control measures, like social distancing and mask wearing, to quantify its absolute effect. Hypothetical lockdown timing was shown to be the critical parameter in ameliorating pandemic peak incidence. More importantly, we found that well-timed lockdowns can split the peak of hospitalizations into two smaller distant peaks while extending the overall pandemic duration. The timing of lockdowns reveals that a "tunneling" effect on incidence can be achieved to bypass the peak and prevent pandemic caseloads from exceeding hospital capacity.

Prevalence and associated factors for needlestick and sharp injuries (NSIs) among dental assistants in Jeddah, Saudi Arabia

BACKGROUND@#Dental personnel are subject to exposure to a number of occupational factors including needlestick and sharp injuries (NSIs). Our study aims to address knowledge gaps on prevalence and associated factors for needlestick and sharp injuries (NSIs) for the first time in Saudi Arabia.@*METHODS@#This cross-sectional study was conducted on a sample of 450 dental assistants recruited from 40 randomly selected private clinics in Jeddah, Saudi Arabia. Data on demographic characteristics, history of NSIs, nature of work, compliance with infection control protocols, and knowledge of infection control procedures and disease transmission were collected using a self-administered questionnaire. Logistic regression analysis was used to assess factors associated with NSIs; unadjusted and adjusted odds ratios (aORs) and their respective 95% confidence intervals (CIs) were computed.@*RESULTS@#About three in ten dental assistants experienced at least one NSI (29.8%, 95% CI 25.6-34.2%) in private dental clinics. Lack of adequate knowledge of infection control procedures and disease transmission, non-compliance with infection control protocol of vaccination against hepatitis B virus, and attending 12 or less number of patients daily were significantly associated with increased risk of NSIs (p ≤ 0.05); adjusted odds ratios (95% CI) were 1.87 (1.18-2.97), 1.89 (1.05-3.41), and 1.63 (1.03-2.56), respectively. In addition, dental assistants working in 45.8% of dental clinics that had no infection control unit were positively associated with higher NSI risk (aOR = 2.28, 95% CI 1.45-3.57).@*CONCLUSION@#Our study reported the prevalent nature of NSIs among dental assistants in Saudi Arabia and identified key factors that could be targeted to mitigate this preventable condition. Dental assistants would benefit from proper training on infection control protocols and procedures.