A Descriptive Study of Nosocomial Infections in an Adult Intensive Care Unit in Fiji: 2011-12

Copyright © 2014 Keshni Naidu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Nosocomial infections in an intensive care unit (ICU) are common and associated with a high mortality but there are no published data from the Oceania region. A retrospective study in Fiji’s largest ICU (2011-12) reported that 114 of a total 663 adult ICU admissions had bacteriological culture-confirmed nosocomial infection. The commonest sites of infection were respiratory and bloodstream. Gram negative bacteria were the commonest pathogens isolated, especially Klebsiella pneumoniae (extended-spectru

‘Power plays plus push’: experts’ insights into the development and implementation of active tuberculosis case-finding policies globally, a qualitative study

Objective: To explore experts’ views on factors influencing national and global active case-finding (ACF) policy development and implementation, and the use of evidence in these processes. Design: This is an exploratory study based on semistructured expert interviews. Framework analysis was applied. Participants: The study involved a purposive sample of 39 experts from international, non-governmental and non-profit organisations, funders, government institutions, international societies, think tanks, universities and research institutions worldwide. Results: This study highlighted the perceived need among experts for different types of evidence for ACF policy development and implementation, and for stakeholder engagement including researchers and policymakers to foster evidence use. Interviewees stressed the influence of government, donor and non-governmental stakeholders in ACF policy development. Such key stakeholders also influence ACF policy implementation, in addition to available systems and processes in a given health system, and implementers’ motivation and incentives. According to the interviewees, the World Health Organization (WHO) guidelines for systematic screening face the innate challenge of providing guidance to countries across the broad area of ACF in terms of target groups, settings and screening algorithms. The guidelines could be improved by focusing on what should be done rather than what can be done in ACF, and by providing howto examples. Leadership, integration into health systems and long-term financing are key for ACF to be sustainable. Conclusions: We provide new insights into ACF policy processes globally, particularly regarding facilitators for and barriers to ACF policy development, evidence need and use, and donor organisations’ influence. According to expert participants, national and global ACF policy development and implementation can be improved by broadening stakeholder engagement. Meanwhile, using diverse evidence to inform ACF policy development and implementation could mitigate the ‘power plays plus push’ that might otherwise disrupt and mislead these policy processes

Factors influencing active tuberculosis case-finding policy development and implementation: a scoping review

ABSTRACT Objective To explore antecedents, components and influencing factors on active case- finding (ACF) policy development and implementation. Design Scoping review, searching MEDLINE, Web of Science, the Cochrane Database of Systematic Reviews and the World Health Organization (WHO) Library from January 1968 to January 2018. We excluded studies focusing on latent tuberculosis (TB) infection, passive case- finding, childhood TB and studies about effectiveness, yield, accuracy and impact without descriptions of how this evidence has/could influence ACF policy or implementation. We included any type of study written in English, and conducted frequency and thematic analyses. Results Seventy- three articles fulfilled our eligibility criteria. Most (67%) were published after 2010. The studies were conducted in all WHO regions, but primarily in Africa (22%), Europe (23%) and the Western- Pacific region (12%). Forty- one percent of the studies were classified as quantitative, followed by reviews (22%) and qualitative studies (12%). Most articles focused on ACF for tuberculosis contacts (25%) or migrants (32%). Fourteen percent of the articles described community- based screening of high- risk populations. Fifty- nine percent of studies reported influencing factors for ACF implementation; mostly linked to the health system (eg, resources) and the community/individual (eg, social determinants of health). Only two articles highlighted factors influencing ACF policy development (eg, politics). Six articles described WHO’s ACF- related recommendations as important antecedent for ACF. Key components of successful ACF implementation include health system capacity, mechanisms for integration, education and collaboration for ACF. Conclusion We identified some main themes regarding the antecedents, components and influencing factors for ACF policy development and implementation. While we know much about facilitators and barriers for ACF policy implementation, we know less about how to strengthen those facilitators and how to overcome those barriers. A major knowledge gap remains when it comes to understanding which contextual factors influence ACF policy development. Research is required to understand, inform and improve ACF policy development and implementation

Retrospective analysis of multidrug-resistanttuberculosis case notifications in Australia (1999-2018)

This study describes the epidemiology and treatment outcomes of multidrug-resistant tuberculosis (MDR-TB) cases notified in Australia between 1999 and 2018, and investigates whether current data fields in the national tuberculosis (TB) dataset allow description and measurement of surveillance information pertaining to the diagnosis and clinical management of MDR-TB

Income security during periods of ill health: A scoping review of policies, practice and coverage in low-income and middle-income countries

The COVID-19 pandemic is a reminder that insufficient income security in periods of ill health leads to economic hardship for individuals and hampers disease control efforts as people struggle to stay home when sick or advised to observe quarantine. Evidence on income security during periods of ill health is growing but has not previously been reviewed as a full body of work concerning low-income and middle-income countries (LMICs). We performed a scoping review to map the range, features, coverage, protective effects and equity of policies that aim to provide income security for adults whose ill health prevents them from participating in gainful work. A total of 134 studies were included, providing data from 95% of LMICs. However, data across the majority of these countries were severely limited. Collectively the included studies demonstrate that coverage of contributory incomesecurity schemes is low, especially for informal and lowincome workers. Meanwhile, non-contributory schemes targeting low-income groups are often not explicitly designed to provide income support in periods of ill health, they can be difficult to access and rarely provide sufficient income support to cover the needs of eligible recipients. While identifying an urgent need for more research on illness-related income security in LMICs, this review concludes that scaling up and diversifying the range of income security interventions is crucial for improving coverage and equity. To achieve these outcomes, illnessrelated income protection must receive greater recognition in health policy and health financing circles, expanding our understanding of financial hardship beyond direct medical costs.Funding for this research was received from the Swedish Research Council (2018–05174)

Spatiotemporal transmission and socio-climatic factors related to paediatric tuberculosis in north-western Ethiopia

The burden of tuberculosis (TB) in children reflects continuing and recent transmission within a population. This study aimed to identify spatiotemporal and socio-climatic factors associated with paediatric TB in north-western Ethiopia. Multivariate Poisson regression models were computed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo simulation. A total of 2,240 children aged under 15 years diagnosed with TB during the years 2013-2016 were included in the analysis. The annual TB incidence rates were 44 and 28 per 100,000 children, for children aged under 15 and 5 years, respectively. Spatial clustering of TB was observed in the border area of north-western Ethiopia. The spatio-temporal transmission of childhood TB was found to be associated with district level socio-climatic factors such as urbanisation [relative risk (RR): 1.8; 95% credible interval (CrI): 1.2, 2.6], lower educational status (RR: 1.5; 95% CrI: 1.0, 2.1), a high percentage of internal migration (RR: 1.3; 95% CrI: 1.0, 1.6), high temperature (RR: 1.3; 95% CrI: 1.0, 1.7) and high rainfall (RR: 1.5; 95% CrI: 1.1, 2.0). We conclude that interventions targeting hotspot districts with a high proportion of childhood TB are important to reduce TB transmission in northwest Ethiopia

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia

Background: Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. Methods: An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS. Results: A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering. Conclusion: Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region

Mapping tuberculosis treatment outcomes in Ethiopia

Background: Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions. Methods: A geospatial analysis was conducted using national TB data reported to the health management information system (HMIS), for the period 2015-2017. The prevalence of poor TB treatment outcomes was calculated by dividing the sum of treatment failure, death and loss to follow-up by the total number of TB patients. Binomial logistic regression models were computed and a spatial analysis was performed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo (MCMC) simulation. Geographic clustering was assessed using the Getis-Ord Gi* statistic, and global and local Moran's I statistics. Results: A total of 223,244 TB patients were reported from 722 districts in Ethiopia during the study period. Of these, 63,556 (28.5%) were cured, 139,633 (62.4%) completed treatment, 6716 (3.0%) died, 1459 (0.7%) had treatment failure, and 12,200 (5.5%) were lost to follow-up. The overall prevalence of a poor TB treatment outcome was 9.0% (range, 1-58%). Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions. Spatial clustering of poor TB treatment outcomes was positively associated with the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature per degree Celsius (OR: 1.15; 95% CI: 1.08, 1.21). Conclusions: This study showed significant spatial variation in poor TB treatment outcomes in Ethiopia that was related to underlying socioeconomic status, knowledge about TB, and climatic conditions. Clinical and public health interventions should be targeted in hot spot areas to reduce poor TB treatment outcomes and to achieve the national End-TB Strategy targets

Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis

Background Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or offer counselling or additional support to patients. The aim of this study was to develop a simple clinical risk score to predict poor treatment outcomes in patients with MDR-TB, using routinely collected data from two large countries in geographically distinct regions. Methods We used MDR-TB data collected from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The data were divided into derivation (n = 343; 60%) and validation groups (n = 227; 40%). A poor treatment outcome was defined as treatment failure, lost to follow up or death. A risk score for poor treatment outcomes was derived using a Cox proportional hazard model in the derivation group. The model was then validated in the validation group. Results The overall rate of poor treatment outcome was 39.5% (n = 225); 37.9% (n = 86) in the derivation group and 40.5% (n = 139) in the validation group. Three variables were identified as predictors of poor treatment outcomes, and each was assigned a number of points proportional to its regression coefficient. These predictors and their points were: 1) history of taking second-line TB treatment (2 points), 2) resistance to any fluoroquinolones (3 points), and 3) smear did not convert from positive to negative at two months (4 points). We summed these points to calculate the risk score for each patient; three risk groups were defined: low risk (0 to 2 points), medium risk (3 to 5 points), and high risk (6 to 9 points). In the derivation group, poor treatment outcomes were reported for these three groups as 14%, 27%, and 71%, respectively. The area under the receiver operating characteristic curve for the point system in the derivation group was 0.69 (95% CI 0.60 to 0.77) and was similar to that in the validation group (0.67; 95% CI 0.56 to 0.78; p = 0.82). Conclusion History of second-line TB treatment, resistance to any fluoroquinolones, and smear non-conversion at two months can be used to estimate the risk of poor treatment outcome in patients with MDR-TB with a moderate degree of accuracy (AUROC = 0.69)

Syndromic surveillance in Vanuatu since Cyclone Pam: a descriptive study.

In 2012, Vanuatu designed and implemented a syndromic surveillance system based on the guidelines developed by the Pacific Community and the World Health Organization to provide early warning of outbreaks and other important public health events. Four core syndromes were endorsed for surveillance: acute fever and rash, prolonged fever, influenza-like illness and acute watery diarrhoea. In March 2015, Vanuatu was struck by Cyclone Pam, after which several important changes and improvements to the country's syndromic surveillance were made. To date, there has been no formal evaluation of whether regular reports are occurring or that core syndromes are being documented. We therefore carried out a descriptive study in the 11 sentinel sites in Vanuatu conducting syndromic surveillance between July and December 2015. There was a total of 53 822 consultations which were higher in the first 13 weeks (n = 29 622) compared with the last 13 weeks (n = 24 200). During the six months, there were no cases of acute fever and rash or prolonged fever. There were cases with influenza-like illness from week 27 to 35, but no case was reported after week 35. Acute watery diarrhoea occurred in one or two cases per week during the whole study period. For these two core syndromes, there were generally more females than males, and about one third were children aged under 5 years. In conclusion, Vanuatu implemented changes to its new syndromic surveillance system from July to December 2015, although laboratory components had not yet been incorporated. The laboratory components are working in 2016 and will be the subject of a further report