Objective: The study aims to determine the factors associated with unsuccessful treatment outcome among patients who have undergone tuberculosis treatment. Methods: An analytic cross-sectional study was employed through secondary data analysis of administrative data collected by the National Tuberculosis Control Program from October 2015 to September 2016. Using multiple logistic regression analysis, factors associated with unsuccessful treatment outcome were determined. Results: Multiple logistic regression analysis revealed that belonging to age groups 25 to 34 (aOR=0.73; 95%CI 0.54-0.99) or 35 to 44 (aOR=0.75; 95%CI 0.56-0.99), being male (aOR=1.30; 95%CI 1.03-1.64), doing crafts and related trades work (aOR=0.66; 95%CI 0.46-0.94), living in either a 4th class city (aOR=0.46; 95%CI 0.26-0.82), 1st class municipality (aOR=0.75; 95%CI 0.57-0.98), 4th class municipality (aOR=0.59; 95%CI 0.38-0.93), having a positive sputum smear result (aOR=1.60; 95%CI 1.29-2.00), having rifampicin-resistant/ multidrug-resistant tuberculosis (aOR=9.32; 95%CI 7.28-11.93), being a treatment after lost to follow-up case (aOR=1.84; 95%CI 1.37-2.47) or a case with previously unknown treatment outcome (aOR=1.42; 95%CI 1.00-2.01) were significant correlates of unsuccessful treatment outcome. Conclusion The study found that age, sex, occupation, residence, sputum smear results, drug resistance, and history of previous treatment were associated with unsuccessful treatment outcome.
Philippines ; Tuberculosis, Pulmonary ; Treatment Outcome ; Regression Analysis

Objectives: This scoping review aimed to support a landscape analysis to identify lessons learned about intersectoral collaborations (ISCs) by describing their existing models in the context of dengue, malaria and yellow fever. Methods: A scoping review following the methodology of Joanna Briggs Institute was performed using the following inclusion criteria: studies involving humans; studies discussing intersectoral collaborations, malaria/dengue/yellow fever, and prevention or control at any level; and studies in countries endemic for the aforementioned diseases. Studies were screened using Covidence, while data were extracted using NVivo. Results: Of the 7,535 records retrieved, 69 were included in the qualitative analysis. Most ISCs were initiated by multilateral organizations and ministries of health, and none by communities. Strategies included advocacy, health education, research, public health measures, resource mobilization, service delivery and training; mostly employed on a community level. Monitoring and evaluation were mostly formative, ongoing, and participatory. Gaps included administrative and policy barriers, resource shortages, and inadequate research and training. Conclusions Multiple models of ISC exist in the literature. There is a need to develop a comprehensive framework for an effective and sustainable multisectoral approach for the prevention and control of VBDs ensuring adequate resources, active stakeholders, and strategies that span the entire socio-ecological spectrum.
Dengue ; Disease Vectors ; Intersectoral Collaboration ; Malaria ; Vector Borne Diseases