Development of a multiassay algorithm (MAA) to identify recent HIV infection in newly diagnosed individuals in Indonesia.

Ongoing HIV transmission is a public health priority in Indonesia. We developed a new multiassay algorithm (MAA) to identify recent HIV infection. The MAA is a sequential decision tree based on multiple biomarkers, starting with CD4+ T cells >200/µL, followed by plasma viral load (pVL) > 1,000 copies/ml, avidity index (AI) < 0 · 7, and pol ambiguity <0 · 47%. Plasma from 140 HIV-infected adults from 19 hospitals across Indonesia (January 2018 - June 2020) was studied, consisting of a training set (N = 60) of longstanding infection (>12-month) and a test set (N = 80) of newly diagnosed (≤1-month) antiretroviral (ARV) drug naive individuals. Ten of eighty (12 · 5%) newly diagnosed individuals were classified as recent infections. Drug resistance mutations (DRMs) against reverse transcriptase inhibitors were identified in two individuals: one infected with HIV subtype C (K219Q, V179T) and the other with CRF01_AE (V179D). Ongoing HIV transmission, including infections with DRMs, is substantial in Indonesia.

Epidemiologic, clinical, and serum markers may improve discrimination between bacterial and viral etiologies of childhood pneumonia.

Background: Discrimination of bacterial and viral etiologies of childhood community-acquired pneumonia (CAP) is often challenging. Unnecessary antibiotic administration exposes patients to undue risks and may engender antimicrobial resistance. This study aimed to develop a prediction model using epidemiological, clinical and laboratory data to differentiate between bacterial and viral CAP. Methods: Data from 155 children with confirmed bacterial or mixed bacterial and viral infection (N = 124) and viral infection (N = 31) were derived from a comprehensive assessment of causative pathogens [Partnerships for Enhanced Engagement in Research-Pneumonia in Pediatrics (PEER-PePPeS)] conducted in Indonesia. Epidemiologic, clinical and biomarker profiles (hematology and inflammatory markers) were compared between groups. The area under the receiver operating characteristic curve (AUROC) for varying biomarker levels was used to characterize performance and determine cut-off values for discrimination of bacterial and mixed CAP versus viral CAP. Diagnostic predictors of bacterial and mixed CAP were assessed by multivariate logistic regression. Results: Diarrhea was more frequently reported in bacterial and mixed CAP, while viral infections more frequently occurred during Indonesia's rainy season. White blood cell counts (WBC), absolute neutrophil counts (ANC), neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and procalcitonin (PCT) were significantly higher in bacterial and mixed cases. After adjusting for covariates, the following were the most important predictors of bacterial or mixed CAP: rainy season (aOR 0.26; 95% CI 0.08-0.90; p = 0.033), CRP ≥5.70 mg/L (aOR 4.71; 95% CI 1.18-18.74; p = 0.028), and presence of fever (aOR 5.26; 95% CI 1.07-25.91; p = 0.041). The model assessed had a low R-squared (Nagelkerke R2 = 0.490) but good calibration (p = 0.610 for Hosmer Lemeshow test). The combination of CRP and fever had moderate predictive value with sensitivity and specificity of 62.28 and 65.52%, respectively. Conclusion: Combining clinical and laboratory profiles is potentially valuable for discriminating bacterial and mixed from viral pediatric CAP and may guide antibiotic use. Further studies with a larger sample size should be performed to validate this model.

Epidemiology of community-acquired pneumonia among hospitalised children in Indonesia: a multicentre, prospective study.

OBJECTIVE: To identify aetiologies of childhood community-acquired pneumonia (CAP) based on a comprehensive diagnostic approach. DESIGN: 'Partnerships for Enhanced Engagement in Research-Pneumonia in Paediatrics (PEER-PePPeS)' study was an observational prospective cohort study conducted from July 2017 to September 2019. SETTING: Government referral teaching hospitals and satellite sites in three cities in Indonesia: Semarang, Yogyakarta and Tangerang. PARTICIPANTS: Hospitalised children aged 2-59 months who met the criteria for pneumonia were eligible. Children were excluded if they had been hospitalised for >24 hours; had malignancy or history of malignancy; a history of long-term (>2 months) steroid therapy, or conditions that might interfere with compliance with study procedures. MAIN OUTCOMES MEASURES: Causative bacterial, viral or mixed pathogen(s) for pneumonia were determined using microbiological, molecular and serological tests from routinely collected specimens (blood, sputum and nasopharyngeal swabs). We applied a previously published algorithm (PEER-PePPeS rules) to determine the causative pathogen(s). RESULTS: 188 subjects were enrolled. Based on our algorithm, 48 (25.5%) had a bacterial infection, 31 (16.5%) had a viral infection, 76 (40.4%) had mixed bacterial and viral infections, and 33 (17.6%) were unable to be classified. The five most common causative pathogens identified were Haemophilus influenzae non-type B (N=73, 38.8%), respiratory syncytial virus (RSV) (N=51, 27.1%), Klebsiella pneumoniae (N=43, 22.9%), Streptococcus pneumoniae (N=29, 15.4%) and Influenza virus (N=25, 13.3%). RSV and influenza virus diagnoses were highly associated with Indonesia's rainy season (November-March). The PCR assays on induced sputum (IS) specimens captured most of the pathogens identified in this study. CONCLUSIONS: Our study found that H. influenzae non-type B and RSV were the most frequently identified pathogens causing hospitalised CAP among Indonesian children aged 2-59 months old. Our study also highlights the importance of PCR for diagnosis and by extension, appropriate use of antimicrobials. TRAIL REGISTRATION NUMBER: NCT03366454.