Background: The rapid global spread of SARS-COV-2 forced governments to implement drastic interventions. The existence of a large but undetermined number of mild or non-symptomatic but infectious cases seems to be involved in the rapid spread, creating a high level of uncertainty due to the difficulty to measure them, and difficulty for epidemiologic modelling. Methods: We developed a compartmental model with deterministic equations, that accounts for clinical status, mobility, r heterogenous susceptibility and non-pharmaceutical interventions . The model was calibrated using data from different regions and we used it to predict the dynamic in Buenos Aires Metropolitan Area (AMBA). Results: The model adjusted well to different geographical regions. In AMBA the model predicted 21400 deaths at 300 days, with 27% of the population in the region immunized after the first wave, partly due to the high incidence of asymptomatic cases. The mobility restriction is approximately linear, with any restriction bringing a positive effect. The other interventions have a combined effect of 27% reduction in infection rates. Conclusion: Our research underlines the role of asymptomatic cases in the epidemics' dynamic and introduces the concept of susceptibility heterogeneity as a potential explanation for otherwise unexplained outbreak dynamics. The model also shows the big role of non-pharmaceutical interventions both in slowing down the epidemic dynamics and in reducing the eventual number of deaths. The model results are closely compatible with observed data.

PM2.5 levels affect human health. However, its relationship with other health vulnerability determinants has not been sufficiently explored. Furthermore, public access to PM2.5 datasets, linkable to health statistics, is not available. We built a georeferenced database and map of annual mean PM2.5 emissions and air concentrations values in Argentina in 2010 and explored their correlations with other health vulnerability determinants. We obtained data for montlhy PM2.5 values emissions and air concentrations in Argentina from public sources. We evaluated health vulnerability by the “Sanitary Vulnerability Index (SVI)”. Non-parametric correlations between variables below 0.22, corresponding to a R2=5%, were deemed meaningless. PM2.5 emissions concentrated in urban and intensive agricultural areas of Argentina. PM2.5 air concentrations were acceptable (≤10 microg/m3) in only 15% of the Argentinean territory, respectively. The correlation between air concentration of PM2.5 and human emission was meaningless. Emissions, but not air concentrations correlated >0.22 with indicators of human activity. SVI correlated meaninglessly with PM2.5 air concentration. In conclusion, PM2.5 levels were above acceptable levels in 85% of the Argentinian territory in 2010. The lack of meaningful correlations between PM2.5 and SVI suggest that these coefficients might be used in combination to assess health vulnerability. Further research is warranted.

Antiretroviral therapy changed the prognosis of people living with HIV/AIDS. However, lack of adherence jeopardizes the success of antiretroviral therapy and enhances the development of treatment‐resistant strains, treatment failure, and therefore it stands as a public health problem. The main goal of this study was to measure the impact on treatment discontinuations and lost to follow up, of a telephone follow‐up strategy in naïve patients who start antiretroviral therapy. We conducted a single‐site, cohort study during a 12‐month period (May 2011–May 2012). A prospective cohort of naïve patients received the standard of care plus a specific telephone follow‐up strategy. Results were compared with a retrospective cohort of naïve patients followed up at the same site, who started antiretroviral therapy receiving only the standard of care during a similar period (January–December 2009). We used descriptive statistics and Fisher exact test for the comparisons of variables. We enrolled 41 patients in the prospective cohort and 50 in the retrospective one. Both cohorts had similar general characteristics. We found a lower number of patients who were lost to follow up in the prospective cohort (intervention) consistent with lower rates of treatment abandonment, suspensions and a similar tendency for events, including death, even when none of these findings was statistically significant. Baseline characteristics and main results are shown in the table below. Further randomized studies should be conducted applying a telephone follow‐up strategy to confirm these findings. Non intervention group (n: 50) Intervention Group (n: 41) p Age (mean in years)36350.58Women n (%)17 (34%)23 (56%)0.034Heterosexual n (%)33 (66%)28 (68%)0.81Education, years (mean)10.0210.390.58Preexistent serious disease6 (12%)5 (12%)1Previous opportunistic events (%)16 (32%)10 (24%)0.28Baseline CD4 count, median (range)176 (7–783)222 (20–868)0.12Baseline HIV RNA, log4.894.220.001Abandonment of treatment9 (18%)3 (7%)0.021Change of treatment10 (20%)14 (34%)0.042Lost to follow up23 (46%)10 (24%)0.032Hospitalization after HAART4 (8%)3 (7%)0.3New opportunistic event3 (6%)0 (0%)N/ADeath2 (4%)1 (2.4%)0.41CD4/mm3 at 24 weeks (median)3153840.151Log HIV RNA at 24 weeks (median)1.691.69

Objetivos: Evaluar la influencia de la cuarentena por COVID-19 en variables epidemiológicas clave con respecto a la prevención de la transmisión materno infantil (TMI) del VIH en Ciudad de Buenos Aires (CABA).   Métodos: Análisis retrospectivo de los datos agregados de TMI de las principales maternidades de CABA. El año pandémico (2020) se comparó con los años no pandémicos 2018-2019.   Resultados: Se observó una reducción del total de nacimientos en 2020 en comparación con 2019 y 2018 (11640 vs. 14031 y 15978, respectivamente). La proporción de nacidos vivos en madres VIH+ (MEV) fue 0,88% en 2020 sin diferencia con 2019 y 2018 (0,94% y 0,93%), p> 0,05 para todas las comparaciones. Entre las MEV, el diagnóstico intraparto fue del 2,9% para 2020, sin diferencias con 2019 (2,25%) y 2018 (9,3%), p> 0,05 (todas las comparaciones); el 8,8% comenzó el tratamiento antirretroviral con >28 semanas de edad gestacional en 2020 frente al 16% y el 18,05% en 2018 y 2019 (p> 0,05, todas las comparaciones). La prevalencia de la carga viral indetectable en el momento del parto fue del 67% en 2020 frente al 64% en 2018 y del 65,4% en 2019 (p> 0,05, todas las comparaciones). La transmisión perinatal fue 0% en 2020 vs 1.33% en 2018 y 2.25% 2019 (p> 0.05, todas las comparaciones)   Conclusiones: En la primera ola de la pandemia de COVID 19 no se observó ningún impacto perjudicial en la proporción de MEV asistidas, diagnóstico intraparto de VIH, inicio tardío del TARV y TMI en CABA.

Background: Calibration of case-finding algorithms from electronic health records (EHR) against established disease surveillance protocols is key to avoiding misclassification bias when using EHR data in epidemiological research. We examined the agreement in the classification of troponin I levels and identification of cardiac pain in hospital EHR data against manually abstracted charts for hospitalizations observed by the ARIC community surveillance of cardiovascular events. Methods: A structured data request for laboratory data and provider notes was submitted to hospitals in the ARIC community surveillance program. Computer programs were developed to extract dates of service, type of laboratory assays performed, and individual assay values for days 1-4 of each hospitalization. Presence of cardiac pain was extracted from provider notes using natural language processing protocols. We calculated percent agreement for troponin I values, kappa statistics for their classification as abnormal (values ≥ twice upper limit normal (ULN)), equivocal (values ≥ULN, but < twice ULN) normal (<ULN), and incomplete, and validity statistics for cardiac pain. Abstraction of information from the medical records by trained abstractors was considered the “gold standard” for comparisons. The analysis sample consisted of all events eligible for full abstraction discharged from one hospital in 2014. Analytical code was created using a “training” dataset randomly-selected from the analysis sample, with the final results computed using a validation sample. Results: Of the 126 EHRs, 104 were eligible for abstraction of cardiac biomarkers and pain information. Agreement in the troponin I values was 75.5% (95%CI: 65.8%, 83.6%) for day 1 of the hospitalization, decreasing thereafter to 62.5% (95%CI: 24.5%, 91.5%) for Day 4. The kappa coefficient for the classification of troponin I values was 0.96 (95% CI: 0.90, 1.00), We observed a high sensitivity in the abstraction of information on cardiac pain (0.99 (95%CI: 0.94, 1.0)). The specificity of cardiac pain information was 0.24 (95% CI: 0.16, 0.35) when extracted from all note types, increasing to 0.90 (95%CI: 0.75, 0.97) if extracted from discharge notes. Conclusion: Troponin I values and manifestation of ischemia such as cardiac pain are critical to the classification of acute coronary events. Therefore, the observed excellent agreement with the gold standard ARIC abstraction shows promise for the use of EHRs in the surveillance of acute cardiovascular disease.