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 [Formula: see text] formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible [Formula: see text] 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.

Salmonella on Raw Poultry in Retail Markets in Guatemala: Levels, Antibiotic Susceptibility, and Serovar Distribution.

The objective of this study was to determine Salmonella numbers on retail raw chicken carcasses in Guatemala and to phenotypically characterize the isolates (serotyping and antibiotic susceptibility). In total, 300 chicken carcasses were collected from seven departments in Guatemala. Salmonella numbers were determined using the most-probable-number method following the U. S. Department of Agriculture's Food Safety and Inspection Service protocol. In total, 103 isolates were obtained, all of which were tested for antibiotic susceptibility, whereas 46 isolates were serotyped. Overall, Salmonella prevalence and mean number (mean log most probable number per carcass) was 34.3% and 2.3 (95% confidence interval: 2.1 to 2.5), respectively. Significant differences (P < 0.05) in Salmonella prevalence were found by storage condition (refrigerated or ambient temperature), market type (wet markets, supermarkets, and independent poultry stores), chicken production system (integrated or nonintegrated production company), and chicken skin color (white or yellow). Chickens produced by integrated companies had lower Salmonella numbers (P < 0.05) than nonintegrated companies, and white-skin carcasses had lower numbers (P < 0.05) than yellow-skin carcasses. Among 13 different Salmonella serovars identified, Paratyphi B (34.8%) was most prevalent, followed by Heidelberg (16.3%) and Derby (11.6%). Of all the Salmonella isolates, 59.2% were resistant to one to three antibiotics and 13.6% to four or more antibiotics. Among all the serovars obtained, Salmonella Paratyphi B and Heidelberg were the most resistant to the antibiotics tested. Salmonella levels and antibiotic resistant profiles among isolates from raw poultry at the retail market level were high relative to other reports from North and South America. These data can be used by Guatemalan stakeholders to develop risk assessment models and support further research opportunities to control transmission of Salmonella spp. and antibiotic-resistant isolates from chicken meat to humans.

Counts, serovars, and antimicrobial resistance phenotypes of Salmonella on raw chicken meat at retail in Colombia.

The objective of this study was to determine Salmonella counts, serovars, and antimicrobial-resistant phenotypes on retail raw chicken carcasses in Colombia. A total of 301 chicken carcasses were collected from six departments (one city per department) in Colombia. Samples were analyzed for Salmonella counts using the most-probable-number method as recommended by the U.S. Department of Agriculture, Food Safety Inspection Service protocol. A total of 378 isolates (268 from our previous study) were serotyped and tested for antimicrobial susceptibility. The overall Salmonella count (mean log most probable number per carcass ± 95% confidence interval) and prevalence were 2.1 (2.0 to 2.3) and 37%, respectively. There were significant differences (P < 0.05) by Salmonella levels (i.e., counts and prevalence) by storage temperature (i.e., frozen, chilled, or ambient), retail store type (wet markets, supermarkets, and independent markets), and poultry company (chicken produced by integrated or nonintegrated company). Frozen chicken had the lowest Salmonella levels compared with chicken stored at other temperatures, chickens from wet markets had higher levels than those from other retail store types, and chicken produced by integrated companies had lower levels than nonintegrated companies. Thirty-one Salmonella serovars were identified among 378 isolates, with Salmonella Paratyphi B tartrate-positive (i.e., Salmonella Paratyphi B dT+) the most prevalent (44.7%), followed by Heidelberg (19%), Enteritidis (17.7%), Typhimurium (5.3%), and Anatum (2.1%). Of all the Salmonella isolates, 35.2% were resistant to 1 to 5 antimicrobial agents, 24.6% to 6 to 10, and 33.9% to 11 to 15. Among all the serovars obtained, Salmonella Paratyphi B dT+ and Salmonella Heidelberg were the most antimicrobial resistant. Salmonella prevalence was determined to be high, whereas cell numbers were relatively low. These data can be used in developing risk assessment models for preventing the transmission of Salmonella from chicken to humans in Colombia.