Finagle's laws of information: lessons learnt evaluating a complex health intervention in Nigeria.

Evaluations cannot support evidence-informed decision making if they do not provide the information needed by decision-makers. In this article, we reflect on our own difficulties evaluating the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) approach, an intervention that provides high-resolution demographic and geographical information to support health service delivery. GRID3 was implemented in Nigeria's northern states to support polio (2012-2019) and measles immunisation campaigns (2017-2018). Generalising from our experience we argue that Finagle's four laws of information capture a particular set of challenges when evaluating complex interventions: the weak causal claims derived from quasi-experimental studies and secondary analyses of existing data (the information we have is not the data we want); the limited external validity of counterfactual impact evaluations (the information we want is not the information we need); the absence of reliable monitoring data on implementation processes (the information we need is not what we can obtain) and the overly broad scope of evaluations attempting to generate both proof of concept and evidence for upscaling (the information we can obtain costs more than we want to pay). Evaluating complex interventions requires a careful selection of methods, thorough analyses and balanced judgements. Funders, evaluators and implementers share a joint responsibility for their success.

Metagenomic next-generation sequencing aids the diagnosis of viral infections in febrile returning travellers.

OBJECTIVES: Travel-associated infections are challenging to diagnose because of the broad spectrum of potential aetiologies. As a proof-of-principle study, we used MNGS to identify viral pathogens in clinical samples from returning travellers in a single center to explore its suitability as a diagnostic tool. METHODS: Plasma samples from 40 returning travellers presenting with a fever of ≥38°C were sequenced using MNGS on the Illumina MiSeq platform and compared with standard-of-care diagnostic assays. RESULTS: In total, 11/40 patients were diagnosed with a viral infection. Standard of care diagnostics revealed 5 viral infections using plasma samples; dengue virus 1 (n = 2), hepatitis E (n = 1), Ebola virus (n = 1) and hepatitis A (n = 1), all of which were detected by MNGS. Three additional patients with Chikungunya virus (n = 2) and mumps virus were diagnosed by MNGS only. Respiratory infections detected by nasal/throat swabs only were not detected by MNGS of plasma. One patient had infection with malaria and mumps virus during the same admission. CONCLUSIONS: MNGS analysis of plasma samples improves the sensitivity of diagnosis of viral infections and has potential as an all-in-one diagnostic test. It can be used to identify infections that have not been considered by the treating physician, co-infections and new or emerging pathogens. SUMMARY: Next generation sequencing (NGS) has potential as an all-in-one diagnostic test. In this study we used NGS to diagnose returning travellers with acute febrile illness in the UK, highlighting cases where the diagnosis was missed using standard methods.