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Abstract Background Emergency medical services (EMS) are paramount to boosting health indices in lower-middle income countries (LMICs); however, lack of uniform data collection and analysis hinders system improvement efforts. In the present study, we describe patterns of EMS utilization in the Republic of Armenia and provide key insight into the quality of digital data collection methods. Results For calls logged in the capital city, Yerevan, the majority had at least one missing field. The predominant complaint was high blood pressure among adults (34.4%) and fever among pediatrics (65.9%). A majority of patients were female (57.6%), adults (90.2%), and not transported to a hospital (85.0%). In the rural provinces, the data was largely intact. The predominant complaints were unspecified acute condition (27.4%) and high blood pressure (26.2%) among adults, and fever (43.9%) and unspecified acute condition (22.1%) among pediatrics. A majority of patients were female (57.1%), adults (94.2%), and not transported to a hospital (78.9%). Conclusions Our study reveals that the majority of calls to the EMS system are for concerns not needing in-hospital treatment and for acute exacerbation of chronic conditions. Our study also provides a critical foundation for the improvement of EMS systems in Armenia and in other nations in transition. The Locator software has the potential to be a valuable tool to the MoH if it is improved for surveillance purposes, and future synchronization of digital systems would provide easy access to critical information on population health needs and the effectiveness of public health interventions.

IntroductionThe success of health education programs heavily depends on the individuals' ability to comprehend information and apply it when making decisions regarding health. Low health literacy can lead to poor health in the context of both chronic and infectious diseases, as it influences a range of health-related behaviors. Little is known about infectious disease-related health literacy in Armenia and countries of similar socio-economic profiles. We aimed to quantify the levels of infectious disease-related health literacy and knowledge among the Armenian population and explore the underlying socio-economic factors.Materials and methodsWe conducted a nationwide phone survey among 3483 adults selected via stratified two-stage probability proportional to size sampling in 2021. Descriptive statistics, simple and multivariable regression were used for the analysis.ResultsThe average age of respondents was 49.5 years. The majority were female (71.0%) and had at least 12 years of schooling (70.5%). The mean literacy score was 5.64 out of 7 (SD:1.06). The mean infectious disease knowledge score was 2.48 out of 4 (SD:1.19). Younger age, female gender, higher level of education, city residence, being employed, and having higher monthly expenditures were associated with higher mean scores of infectious disease-related health literacy and knowledge. In multivariable linear regression analysis, all the socio-demographic characteristics remained significant for both dependent variables.ConclusionsThe study results revealed population groups with a higher infectious disease-related health literacy and knowledge. Interventions should focus on groups lagging behind to engage them in proper prevention practices to protect themselves and improve health status of Armenian population.

Advances in vaccinology have resulted in various new vaccines being introduced into recommended immunization schedules. Armenia introduced the rotavirus vaccine (RV) and the pneumococcal conjugate vaccine (PCV) into its national schedule in 2012 and 2014, respectively. Using data from the Armenia Demographic and Health Survey, the uptake of the RV and the PCV among children aged younger than three years was estimated. Multilevel logistic regression models were used to evaluate individual- and community-level factors associated with uptake. Intra-cluster correlations were estimated to explain variations in uptake between clusters. The uptake proportionof each RV dose were 90.0% and 86.6%, while each PCV dose had values of 83.5%, 79.4%, and 75.5%, respectively. Non-uptake was highest among children less than 6 months old, children with one sibling, children from a wealthy family, or children whose living distance to a health clinic was problematic. Significant variability in non-uptake due to cluster differences was found for both RV doses (30.5% and 22.8%, respectively) and for the second PCV dose (53.9%). When developing strategies for new vaccine implementation, characteristics of the child, such as age, siblingship, and distance to a health clinic or residence, should be considered. Further exploration of cluster differences may provide insights based on the increased uptake of these and other new vaccines.

IntroductionSocial network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evaluate the utility of the NHBS HET cycle data for network analysis; 2) to apply statistical analysis in support of previous HIV research, as well as to develop new research results focused on demographic variables and prevention/intervention with respect to heterosexual HIV risk; and 3) to employ NHBS data to inform policy with respect to the EHE plan.MethodWe used data from the 2016 NHBS HET4 (DC). A total of 747 surveys were collected. We used the free social-network analysis package, GEPHI, for all network visualization using adjacency matrix representation. We additionally conducted logistic regression analysis to examine the association of selected variables with HIV status in three models representing 1) demographic and economic effects, 2) behavioral effects, and 3) prevention-intervention effects.ResultsThe results showed 3% were tested positive. Seed 1 initiated the largest networks with 426 nodes (15 positives); seed 4 with 273 nodes (6 positives). Seed 3 had 35 nodes (2 positives). All 23 HIV diagnoses were recruited from 4 zip-codes across DC. The risk of testing positive was higher among people high-school dropouts (Relative Risk (RR) (25.645); 95 CI% 5.699, 115.987), unemployed ((4.267); 1.295, 14.064), returning citizens ((14.319); 4.593, 44.645). We also found in the final model higher association of pre-exposure prophylaxis (PrEP) awareness among those tested negative ((4.783); 1.042, 21.944) and HIV intervention in the past 12 months with those tested positive ((17.887); 2.350,136.135).ConclusionThe network visualization was used to address the primary aim of the analysis-evaluate the success of the implementation of the NHBS as a social network strategy to find new diagnoses. NHBS remains one of the strongest behavioral supplements for DC's HIV planning activities. As part of the evaluation process our analysis helps to understand the impact of demographic, behavioral, and prevention efforts on peoples' HIV status. We strongly recommend other jurisdictions use network visualizations to evaluate the efficacy in reaching hidden populations.