A novel A/H1N1 virus is the cause of the present influenza pandemic; vaccination is a key countermeasure, however, few data assessing prior seasonal vaccine effectiveness (VE) against the pandemic ...strain of H1N1 (pH1N1) virus are available.
Surveillance of influenza-related medical encounter data of active duty military service members stationed in the United States during the period of April-October 2009 with comparison of pH1N1-confirmed cases and location and date-matched controls. Crude odds ratios (OR) and VE estimates for immunized versus non-immunized were calculated as well as adjusted OR (AOR) controlling for sex, age group, and history of prior influenza vaccination. Separate stratified VE analyses by vaccine type (trivalent inactivated TIV or live attenuated LAIV), age groups and hospitalization status were also performed. For the period of April 20 to October 15, 2009, a total of 1,205 cases of pH1N1-confirmed cases were reported, 966 (80%) among males and over one-half (58%) under 25 years of age. Overall VE for service members was found to be 45% (95% CI, 33 to 55%). Immunization with prior season's TIV (VE = 44%, 95% CI, 32 to 54%) as well as LAIV (VE = 24%, 95% CI, 6 to 38%) were both found to be associated with protection. Of significance, VE against a severe disease outcome was higher (VE = 62%, 95% CI, 14 to 84%) than against milder outcomes (VE = 42%, 95% CI, 29 to 53%).
A moderate association with protection against clinically apparent, laboratory-confirmed Pandemic (H1N1) 2009-associated illness was found for immunization with either TIV or LAIV 2008-09 seasonal influenza vaccines. This association with protection was found to be especially apparent for severe disease as compared to milder outcome, as well as in the youngest and older populations. Prior vaccination with seasonal influenza vaccines in 2004-08 was also independently associated with protection.
We evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval ...sites in Peru during 2007-2011. The 3 algorithms' detection sensitivity was 100%, specificity was 97%-99%, and positive predictive value was 27%-46%.
While studying chronic verruga peruana infections in Peru from 2003, we isolated a novel Bartonella agent, which we propose be named Candidatus Bartonella ancashi. This case reveals the inherent ...weakness of relying solely on clinical syndromes for diagnosis and underscores the need for a new diagnostic paradigm in developing settings.
BACKGROUND
The objective of this study was to determine the rates and predictors of non‐AIDS‐defining cancers (NADCs) among a cohort of human immunodeficiency virus (HIV)‐infected individuals.
...METHODS
The authors conducted a retrospective study of 4144 HIV‐infected individuals who had 26,916 person‐years of follow‐up and who had open access to medical care at 1 of the United States military HIV clinics during the years 1988–2003. Cancer incidence rates were race specific and were adjusted for age; these were compared with national rates using logistic regression to assess predictors of NADC development.
RESULTS
One hundred thirty‐three NADCs were diagnosed with a rate of 980 diagnoses per 100,000 person‐years. The most frequent NADCs were skin carcinomas (basal cell and squamous cell), Hodgkin disease, and anal carcinoma. The results showed that there were higher rates of melanoma, basal and squamous cell skin carcinomas, anal carcinoma, prostate carcinoma, and Hodgkin disease among the HIV‐infected cohort compared with age‐adjusted rates for the general United States population. Predictors of NADCs included age older than 40 years (odds ratio OR, 12.2; P < 0.001), Caucasian/non‐Hispanic race (OR, 2.1; P < 0.001), longer duration of HIV infection (OR, 1.2; P < 0.001), and a history of opportunistic infection (OR, 2.5; P < 0.001). The use of highly active antiretroviral therapy (HAART) was associated with lower rates of NADCs (OR, 0.21; P < 0.001). A low CD4 nadir or CD4 count at diagnosis (< 200 cells/mL) was not predictive of NADCs.
CONCLUSIONS
The most frequent NADCs were primary skin malignancies. Melanoma, basal and squamous cell skin carcinomas, anal carcinoma, prostate carcinoma, and Hodgkin disease occurred at higher rates among HIV‐infected individuals. The implementation of screening programs for these malignancies should be considered. Most risk factors for the development of NADCs are nonmodifiable; however, the use of HAART appeared to be beneficial in protecting against the development of malignant disease. Cancer 2005. Published 2005 by the American Cancer Society.
The most common non‐AIDS‐defining cancers among patients who were infected with the human immunodeficiency virus (HIV) were primary skin malignancies. Melanoma, basal cell and squamous cell skin carcinomas, anal carcinoma, prostate carcinoma, and Hodgkin disease occurred at higher rates among HIV‐infected individuals. The implementation of screening programs for these cancers should be considered.
Public health surveillance is undergoing a revolution driven by advances in the field of information technology. Many countries have experienced vast improvements in the collection, ingestion, ...analysis, visualization, and dissemination of public health data. Resource-limited countries have lagged behind due to challenges in information technology infrastructure, public health resources, and the costs of proprietary software. The Suite for Automated Global Electronic bioSurveillance (SAGES) is a collection of modular, flexible, freely-available software tools for electronic disease surveillance in resource-limited settings. One or more SAGES tools may be used in concert with existing surveillance applications or the SAGES tools may be used en masse for an end-to-end biosurveillance capability. This flexibility allows for the development of an inexpensive, customized, and sustainable disease surveillance system. The ability to rapidly assess anomalous disease activity may lead to more efficient use of limited resources and better compliance with World Health Organization International Health Regulations.
BackgroundPrevious studies have observed that countries with the strongest levels of pandemic preparedness capacities experience the greatest levels of COVID-19 burden. However, these analyses have ...been limited by cross-country differentials in surveillance system quality and demographics. Here, we address limitations of previous comparisons by exploring country-level relationships between pandemic preparedness measures and comparative mortality ratios (CMRs), a form of indirect age standardisation, of excess COVID-19 mortality.MethodsWe indirectly age standardised excess COVID-19 mortality, from the Institute for Health Metrics and Evaluation modelling database, by comparing observed total excess mortality to an expected age-specific COVID-19 mortality rate from a reference country to derive CMRs. We then linked CMRs with data on country-level measures of pandemic preparedness from the Global Health Security (GHS) Index. These data were used as input into multivariable linear regression analyses that included income as a covariate and adjusted for multiple comparisons. We conducted a sensitivity analysis using excess mortality estimates from WHO and The Economist.ResultsThe GHS Index was negatively associated with excess COVID-19 CMRs (table 2; β= −0.21, 95% CI= −0.35 to −0.08). Greater capacities related to prevention (β= −0.11, 95% CI= −0.22 to −0.00), detection (β= −0.09, 95% CI= −0.19 to −0.00), response (β = −0.19, 95% CI= −0.36 to −0.01), international commitments (β= −0.17, 95% CI= −0.33 to −0.01) and risk environments (β= −0.30, 95% CI= −0.46 to −0.15) were each associated with lower CMRs. Results were not replicated using excess mortality models that rely more heavily on reported COVID-19 deaths (eg, WHO and The Economist).ConclusionThe first direct comparison of COVID-19 excess mortality rates across countries accounting for under-reporting and age structure confirms that greater levels of preparedness were associated with lower excess COVID-19 mortality. Additional research is needed to confirm these relationships as more robust national-level data on COVID-19 impact become available.
Understanding the role of pandemic preparedness during the COVID-19 crisis is challenging considering substantial cross-country gaps in data sources, heterogeneity in reporting of COVID-19 outcomes ...and differences in population age structures and healthcare delivery systems. ...this may be the most well-specified model considering that the residuals are substantially closer to being constant (studentised Breusch-Pagan (BPT=6.91; p=0.075)). Table 1 Country-level effect sizes of 2021 Global Health Security measures on comparative excess mortality ratio Coefficient (95% CI) P value Global Health Security Score −0.17 (−0.32 to −0.03) 0.0168* Prevention score −0.07 (−0.17 to 0.03) 0.1580 Detection score −0.09 (−0.16 to −0.02) 0.0187* Response score −0.11 (−0.27 to 0.04) 0.1612 Health system score −0.06 (−0.18 to 0.06) 0.3086 International norms score −0.13 (−0.26 to −0.01) 0.0407* Risk environment score −0.25 (−0.40 to −0.10) 0.0014* Effect sizes compare a 5-score difference in each index. ...taking into account age likely already adjusts for a substantial proportion of country-level income considering the very strong correlation between log income and fraction of population 65 years and greater in 2019 (Pearson’s r=0.74).
Following the 2009 influenza A/H1N1 (pH1N1) pandemic, both seasonal and pH1N1 viruses circulated in the US during the 2010-2011 influenza season; influenza vaccine effectiveness (VE) may vary between ...live attenuated (LAIV) and trivalent inactivated (TIV) vaccines as well as by virus subtype.
Vaccine type and virus subtype-specific VE were determined for US military active component personnel for the period of September 1, 2010 through April 30, 2011. Laboratory-confirmed influenza-related medical encounters were compared to matched individuals with a non-respiratory illness (healthy controls), and unmatched individuals who experienced a non-influenza respiratory illness (test-negative controls). Odds ratios (OR) and VE estimates were calculated overall, by vaccine type and influenza subtype.
A total of 603 influenza cases were identified. Overall VE was relatively low and similar regardless of whether healthy controls (VE = 26%, 95% CI: -1 to 45) or test-negative controls (VE = 29%, 95% CI: -6 to 53) were used as comparison groups. Using test-negative controls, vaccine type-specific VE was found to be higher for TIV (53%, 95% CI: 25 to 71) than for LAIV (VE = -13%, 95% CI: -77 to 27). Influenza subtype-specific analyses revealed moderate protection against A/H3 (VE = 58%, 95% CI: 21 to 78), but not against A/H1 (VE = -38%, 95% CI: -211 to 39) or B (VE = 34%, 95% CI: -122 to 80).
Overall, a low level of protection against clinically-apparent, laboratory-confirmed, influenza was found for the 2010-11 seasonal influenza vaccines. TIV immunization was associated with higher protection than LAIV, however, no protection against A/H1 was noted, despite inclusion of a pandemic influenza strain as a vaccine component for two consecutive years. Vaccine virus mismatch or lower immunogenicity may have contributed to these findings and deserve further examination in controlled studies. Continued assessment of VE in military personnel is essential in order to better inform vaccination policy decisions.
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