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ObjectiveTo establish seasonal and alert thresholds and transmission intensity categories for influenza to provide timely triggers for preventive measures or upscaling control measures in Cambodia.MethodsUsing Cambodia’s influenza-like illness (ILI) and laboratory-confirmed influenza surveillance data from 2009 to 2015, three parameters were assessed to monitor influenza activity: the proportion of ILI patients among all outpatients, proportion of ILI samples positive for influenza and the product of the two. With these parameters, four threshold levels (seasonal, moderate, high and alert) were established and transmission intensity was categorized based on a World Health Organization alignment method. Parameters were compared against their respective thresholds.ResultsDistinct seasonality was observed using the two parameters that incorporated laboratory data. Thresholds established using the composite parameter, combining syndromic and laboratory data, had the least number of false alarms in declaring season onset and were most useful in monitoring intensity. Unlike in temperate regions, the syndromic parameter was less useful in monitoring influenza activity or for setting thresholds.ConclusionInfluenza thresholds based on appropriate parameters have the potential to provide timely triggers for public health measures in a tropical country where monitoring and assessing influenza activity has been challenging. Based on these findings, the Ministry of Health plans to raise general awareness regarding influenza among the medical community and the general public. Our findings have important implications for countries in the tropics/subtropics and in resource-limited settings, and categorized transmission intensity can be used to assess severity of potential pandemic influenza as well as seasonal influenza.

Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. The magnitude of the disparity is unclear, however, because race/ethnicity information is often missing in surveillance data. In this study, we quantified the burden of SARS-CoV-2 infection, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias-adjustment for misclassification. After bias-adjustment, the magnitude of the absolute racial/ethnic disparity, measured as the difference in infection rates between classified Black and Hispanic persons compared to classified White persons, increased 1.3-fold and 1.6-fold respectively. These results highlight that complete case analyses may underestimate absolute disparities in infection rates. Collecting race/ethnicity information at time of testing is optimal. However, when data are missing, combined imputation and bias-adjustment improves estimates of the racial/ethnic disparities in the COVID-19 burden.

IntroductionAcute respiratory infections (ARI), including influenza, comprise a leading cause of morbidity and mortality worldwide. Influenza surveillance provides important information to inform policy on influenza control and vaccination. While the epidemiology of influenza has been well characterized in western countries, few data exist on influenza epidemiology in the Eastern Mediterranean Region. We describe the epidemiology of influenza virus in Oman.MethodsUsing syndromic case definitions and protocols, patients from four regional hospitals in Oman were enrolled in a descriptive prospective study to characterize the burden of severe acute respiratory infections (SARI) and influenza. Eligible patients provided demographic information as well as oropharyngeal (OP) and nasopharyngeal (NP) swabs. Specimens were tested for influenza A and influenza B; influenza A viruses were subtyped using RT-PCR.ResultsFrom January 2008 through June 2013, a total of 5,147 cases were enrolled and tested for influenza. Influenza strains were detected in 8% of cases for whom samples were available. Annual incidence rates ranged from 0.5 to 15.4 cases of influenza-associated SARI per 100,000 population. The median age of influenza patients was 6 years with children 0–2 years accounting for 34% of all influenza-associated hospitalizations. By contrast, the median age of non-influenza SARI cases was 1 year with children 0–2 years comprising 59% of SARI. Compared to non-influenza SARI cases, a greater proportion of influenza cases had pre-existing chronic conditions and underwent ventilation during hospitalization.ConclusionsInfluenza virus is associated with a substantial proportion of SARI in Oman. Influenza in Oman approximately follows northern hemisphere seasonality, with major peaks in October to December and a lesser peak around April. The burden of influenza was greatest in children and the elderly. Future efforts should examine the burden of influenza in other potential risk groups such as pregnant women to inform interventions including targeted vaccination.

IntroductionAcute Respiratory Infections (ARI) are responsible for nearly two million childhood deaths worldwide. A limited number of studies have been published on the epidemiology of viral respiratory pathogens in Egypt.MethodsA total of 6113 hospitalized patients >1 month of age with suspected ARI were enrolled between June 23, 2009 and December 31, 2013. Naso‐ and oropharyngeal specimens were collected and tested for influenza A and B, respiratory syncytial virus, human metapneumovirus, adenovirus, and parainfluenza viruses 1–3. Blood specimens from children 1–11 months were cultured and bacterial growth was identified by polymerase chain reaction. Results from a healthcare utilization survey on the proportion of persons seeking care for ARI was used to calculate adjusted ARI incidence rates in the surveillance population.ResultsThe proportion of patients with a viral pathogen detected decreased with age from 67% in patients age 1–11 months to 19% in patients ≥65 years of age. Influenza was the dominant viral pathogen detected in patients ≥1 year of age (13.9%). The highest incidence rates for hospitalized ARI were observed in children 1–11 months (1757.9–5537.5/100 000 population) and RSV was the most commonly detected pathogen in this age group.ConclusionIn this study population, influenza is the largest viral contributor to hospitalized ARIs and children 1–11 months of age experience a high rate of ARI hospitalizations. This study highlights a need for surveillance of additional viral pathogens and alternative detection methods for bacterial pathogens, which may reveal a substantial proportion of as yet unidentified etiologies in adults.

Objectives To examine the impact of a successful 12 month behavioral intervention to improve diabetes control on healthcare utilization in American Samoa. Methods A cluster randomized design was used to assign 268 diabetes patients to a nurse-community health worker (CHW) intervention or usual care. Hospitalizations, emergency department (ED) and primary care physician (PCP) visits were collected retrospectively for one year prior to, and during, the intervention to assess changes in healthcare utilization. The association of utilization changes with change in HbA1c during the intervention was assessed. Results Adjusted incidence rate ratios (RR) for PCP visits were significantly higher in the CHW relative to the usual care group (RR= 1.71; 95% CI, 1.25–2.33). There was no main intervention effect on ED utilization, but visits in the prior year modified the intervention effect on ED visits. Increased PCP utilization was associated with greater decreases in HbA1c (b=−0.10, se=0.04, p=0.01). Conclusions A culturally adapted CHW diabetes intervention in American Samoa significantly increased PCP visits, and decreased ED visits among those with high ED usage in the prior year. These changes suggest important and beneficial impacts on health system utilization from the diabetes intervention in a low resource and high-risk population.

Background: Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data. Methods: We quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification. Results: The ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons. Conclusions: These results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden.

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