IntroductionWith COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities.MethodsIn seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns.ResultsBetween March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate.ConclusionSlum residents’ ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need to ensure that costs do not escalate and unfairly disadvantage slum communities. Remote consulting to reduce face-to-face contact and provision of mental health and gender-based violence services should be considered.

ObjectiveTo measure test accuracy of non-invasive prenatal testing (NIPT) for Down, Edwards and Patau syndromes using cell-free fetal DNA and identify factors affecting accuracy.DesignSystematic review and meta-analysis of published studies.Data sourcesPubMed, Ovid Medline, Ovid Embase and the Cochrane Library published from 1997 to 9 February 2015, followed by weekly autoalerts until 1 April 2015.Eligibility criteria for selecting studiesEnglish language journal articles describing case–control studies with ≥15 trisomy cases or cohort studies with ≥50 pregnant women who had been given NIPT and a reference standard.Results41, 37 and 30 studies of 2012 publications retrieved were included in the review for Down, Edwards and Patau syndromes. Quality appraisal identified high risk of bias in included studies, funnel plots showed evidence of publication bias. Pooled sensitivity was 99.3% (95% CI 98.9% to 99.6%) for Down, 97.4% (95.8% to 98.4%) for Edwards, and 97.4% (86.1% to 99.6%) for Patau syndrome. The pooled specificity was 99.9% (99.9% to 100%) for all three trisomies. In 100 000 pregnancies in the general obstetric population we would expect 417, 89 and 40 cases of Downs, Edwards and Patau syndromes to be detected by NIPT, with 94, 154 and 42 false positive results. Sensitivity was lower in twin than singleton pregnancies, reduced by 9% for Down, 28% for Edwards and 22% for Patau syndrome. Pooled sensitivity was also lower in the first trimester of pregnancy, in studies in the general obstetric population, and in cohort studies with consecutive enrolment.ConclusionsNIPT using cell-free fetal DNA has very high sensitivity and specificity for Down syndrome, with slightly lower sensitivity for Edwards and Patau syndrome. However, it is not 100% accurate and should not be used as a final diagnosis for positive cases.Trial registration numberCRD42014014947.

BackgroundChronic airway diseases pose a big challenge to health systems in most developing countries, particularly in Sub-Saharan Africa. A diagnosis for people with chronic or persistent cough is usually delayed because of individual and health system barriers. However, delayed diagnosis and treatment facilitates further transmission, severity of disease with complications and mortality. The objective of this study is to assess the cost-effectiveness of the practical approach to lung health strategy, a patient-centred approach for diagnosis and treatment of common respiratory illnesses in primary healthcare settings, as a means of strengthening health systems to improve the quality of management of respiratory diseases.Methods/designEconomic evaluation nested in a cluster randomised controlled trial with three arms will be performed. Measures of effectiveness and costs for all arms of the study will be obtained from the cluster randomised controlled clinical trial. The main outcome measures are a combined rate of major respiratory diseases milestones and process indicators extracted from the practical approach to lung health strategy. For analysis, descriptive as well as regression techniques will be used. A cost-effectiveness analysis will be performed according to intention-to-treat principle and from a societal perspective. Cost-effectiveness ratios will be calculated using bootstrapping techniques.DiscussionWe hope to demonstrate the cost-effectiveness of the practical approach to lung health and informal healthcare providers, see an improvement in patients’ quality of life, achieve a reduction in the duration and occurrence of episodes and the chronicity of respiratory diseases, and are able to report a decrease in the social cost. If the practical approach to lung health and informal healthcare provider’s interventions are cost-effective, they could be scaled up to all primary healthcare centres.Trial registrationPACTR: PACTR201411000910192

BackgroundFebrile neutropenia (FN) occurs following myelosuppressive chemotherapy and is associated with morbidity, mortality, costs, and chemotherapy reductions and delays. Granulocyte colony-stimulating factors (G-CSFs) stimulate neutrophil production and may reduce FN incidence when given prophylactically following chemotherapy.MethodsA systematic review and meta-analysis assessed the effectiveness of G-CSFs (pegfilgrastim, filgrastim or lenograstim) in reducing FN incidence in adults undergoing chemotherapy for solid tumours or lymphoma. G-CSFs were compared with no primary G-CSF prophylaxis and with one another. Nine databases were searched in December 2009. Meta-analysis used a random effects model due to heterogeneity.ResultsTwenty studies compared primary G-CSF prophylaxis with no primary G-CSF prophylaxis: five studies of pegfilgrastim; ten of filgrastim; and five of lenograstim. All three G-CSFs significantly reduced FN incidence, with relative risks of 0.30 (95% CI: 0.14 to 0.65) for pegfilgrastim, 0.57 (95% CI: 0.48 to 0.69) for filgrastim, and 0.62 (95% CI: 0.44 to 0.88) for lenograstim. Overall, the relative risk of FN for any primary G-CSF prophylaxis versus no primary G-CSF prophylaxis was 0.51 (95% CI: 0.41 to 0.62). In terms of comparisons between different G-CSFs, five studies compared pegfilgrastim with filgrastim. FN incidence was significantly lower for pegfilgrastim than filgrastim, with a relative risk of 0.66 (95% CI: 0.44 to 0.98).ConclusionsPrimary prophylaxis with G-CSFs significantly reduces FN incidence in adults undergoing chemotherapy for solid tumours or lymphoma. Pegfilgrastim reduces FN incidence to a significantly greater extent than filgrastim.

In economic evaluation, mathematical models have a central role as a way of integrating all the relevant information about a disease and health interventions, in order to estimate costs and consequences over an extended time horizon. Models are based on scientific knowledge of disease (which is likely to change over time), simplifying assumptions and input parameters with different levels of uncertainty; therefore, it is sensible to explore the consistency of model predictions with observational data. Calibration is a useful tool for estimating uncertain parameters, as well as more accurately defining model uncertainty (particularly with respect to the representation of correlations between parameters). Calibration involves the comparison of model outputs (e.g. disease prevalence rates) with empirical data, leading to the identification of model parameter values that achieve a good fit. This article provides guidance on the theoretical underpinnings of different calibration methods. The calibration process is divided into seven steps and different potential methods at each step are discussed, focusing on the particular features of disease models in economic evaluation. The seven steps are (i) Which parameters should be varied in the calibration process? (ii) Which calibration targets should be used? (iii) What measure of goodness of fit should be used? (iv) What parameter search strategy should be used? (v) What determines acceptable goodness-of-fit parameter sets (convergence criteria)? (vi) What determines the termination of the calibration process (stopping rule)? (vii) How should the model calibration results and economic parameters be integrated? The lack of standards in calibrating disease models in economic evaluation can undermine the credibility of calibration methods. In order to avoid the scepticism regarding calibration, we ought to unify the way we approach the problems and report the methods used, and continue to investigate different methods.