Prevalence and predictors of antibiotic prescription among patients hospitalized with viral lower respiratory tract infections in Southern Province, Sri Lanka.

BACKGROUND: Antimicrobial overprescription is common for lower respiratory tract infections (LRTI), as viral and bacterial infections generally present with similar clinical features. Overprescription is associated with downstream antimicrobial resistance. This study aims to identify the prevalence and predictors of antibiotic prescription among patients hospitalized with viral LRTI. METHODS: A prospective cohort study was conducted among patients aged ≥1 year hospitalized with viral LRTI in a tertiary care hospital in Southern Province, Sri Lanka from 2018-2021. Demographic, clinical, and laboratory data were recorded. Nasopharyngeal and blood samples were collected for multiplex polymerase chain reaction testing for 21 respiratory pathogens and procalcitonin (PCT) detection, respectively. Demographic and clinical features associated with antibiotic prescription were identified using Chi Square and t-tests; significant variables (p<0.05) were further included in multivariable logistic regression models. The potential impact of biomarker testing on antibiotic prescription was simulated using standard c-reactive protein (CRP) and PCT cut-offs. RESULTS: Of 1217 patients enrolled, 438 (36.0%) had ≥1 respiratory virus detected, with 48.4% of these patients being male and 30.8% children. Influenza A (39.3%) and human rhinovirus/ enterovirus (28.3%) were most commonly detected. A total of 114 (84.4%) children and 266 (87.8%) adults with respiratory viruses were treated with antibiotics. Among children, neutrophil percentage (median 63.6% vs 47.6%, p = 0.04) was positively associated with antibiotic prescription. Among adults, headache (60.6% vs 35.1%, p = 0.003), crepitations/crackles (55.3% vs 21.6%, p<0.001), rhonchi/wheezing (42.9% vs 18.9%, p = 0.005), and chest x-ray opacities (27.4% vs 8.1%, p = 0.01) were associated with antibiotic prescription. Access to CRP and procalcitonin test results could have potentially decreased inappropriate antibiotic prescription in this study by 89.5% and 83.3%, respectively. CONCLUSIONS: High proportions of viral detection and antibiotic prescription were observed among a large inpatient cohort with LRTI. Increased access to point-of-care biomarker testing may improve antimicrobial prescription.

Study protocol: improving response to malaria in the Amazon through identification of inter-community networks and human mobility in border regions of Ecuador, Peru and Brazil.

INTRODUCTION: Understanding human mobility's role in malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission. METHODS: We measure community connectivity across the study area using a respondent driven sampling design among key informants who are at least 18 years of age. 45 initial communities will be selected: 10 in Brazil, 10 in Ecuador and 25 in Peru. Participants will be recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses will be ranked and the 2-3 most connected communities will then be selected and surveyed. This process will be repeated for a third round of data collection. Community network matrices will be linked with each country's malaria surveillance system to test the effects of mobility on disease risk. ETHICS AND DISSEMINATION: This study protocol has been approved by the institutional review boards of Duke University (USA), Universidad San Francisco de Quito (Ecuador), Universidad Peruana Cayetano Heredia (Peru) and Universidade Federal Minas Gerais (Brazil). Results will be disseminated in communities by the end of the study.

Network Profile: Improving Response to Malaria in the Amazon through Identification of Inter-Community Networks and Human Mobility in Border Regions of Ecuador, Peru, and Brazil.

Objectives: Understanding human mobility's role on malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission. Design: A community-level network survey. Setting: We collect data on community connectivity along three river systems in the Amazon basin: the Pastaza river corridor spanning the Ecuador-Peru border; and the Amazon and Javari river corridors spanning the Brazil-Peru border. Participants: We interviewed key informants in Brazil, Ecuador, and Peru, including from indigenous communities: Shuar, Achuar, Shiwiar, Kichwa, Ticuna, and Yagua. Key informants are at least 18 years of age and are considered community leaders. Primary outcome: Weekly, community-level malaria incidence during the study period. Methods: We measure community connectivity across the study area using a respondent driven sampling design. Forty-five communities were initially selected: 10 in Brazil, 10 in Ecuador, and 25 in Peru. Participants were recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses were ranked and the 2-3 most connected communities were then selected and surveyed. This process was repeated for a third round of data collection. Community network matrices will be linked with eadch country's malaria surveillance system to test the effects of mobility on disease risk. Findings: To date, 586 key informants were surveyed from 126 communities along the Pastaza river corridor. Data collection along the Amazon and Javari river corridors is ongoing. Initial results indicate that network sampling is a superior method to delineate migration flows between communities. Conclusions: Our study provides measures of mobility and connectivity in rural settings where traditional approaches are insufficient, and will allow us to understand mobility's effect on malaria transmission.