Changing food systems and infectious disease risks in low-income and middle-income countries.

The emergence of COVID-19 has drawn the attention of health researchers sharply back to the role that food systems can play in generating human disease burden. But emerging pandemic threats are just one dimension of the complex relationship between agriculture and infectious disease, which is evolving rapidly, particularly in low-income and middle-income countries (LMICs) that are undergoing rapid food system transformation. We examine this changing relationship through four current disease issues. The first is that greater investment in irrigation to improve national food security raises risks of vector-borne disease, which we illustrate with the case of malaria and rice in Africa. The second is that the intensification of livestock production in LMICs brings risks of zoonotic diseases like cysticercosis, which need to be managed as consumer demand grows. The third is that the nutritional benefits of increasing supply of fresh vegetables, fruit, and animal-sourced foods in markets in LMICs pose new food-borne disease risks, which might undermine supply. The fourth issue is that the potential human health risks of antimicrobial resistance from agriculture are intensified by changing livestock production. For each disease issue, we explore how food system transition is creating unintentional infectious disease risks, and what solutions might exist for these problems. We show that successfully addressing all of these challenges requires a coordinated approach between public health and agricultural sectors, recognising the costs and benefits of disease-reducing interventions to both, and seeking win-win solutions that are most likely to attract broad policy support and uptake by food systems.

Examining the effect of evaluation sample size on the sensitivity and specificity of COVID-19 diagnostic tests in practice: a simulation study.

BACKGROUND: In response to the global COVID-19 pandemic, many in vitro diagnostic (IVD) tests for SARS-CoV-2 have been developed. Given the urgent clinical demand, researchers must balance the desire for precise estimates of sensitivity and specificity against the need for rapid implementation. To complement estimates of precision used for sample size calculations, we aimed to estimate the probability that an IVD will fail to perform to expected standards after implementation, following clinical studies with varying sample sizes. METHODS: We assumed that clinical validation study estimates met the 'desirable' performance (sensitivity 97%, specificity 99%) in the target product profile (TPP) published by the Medicines and Healthcare products Regulatory Agency (MHRA). To estimate the real-world impact of imprecision imposed by sample size we used Bayesian posterior calculations along with Monte Carlo simulations with 10,000 independent iterations of 5,000 participants. We varied the prevalence between 1 and 15% and the sample size between 30 and 2,000. For each sample size, we estimated the probability that diagnostic accuracy would fail to meet the TPP criteria after implementation. RESULTS: For a validation study that demonstrates 'desirable' sensitivity within a sample of 30 participants who test positive for COVID-19 using the reference standard, the probability that real-world performance will fail to meet the 'desirable' criteria is 10.7-13.5%, depending on prevalence. Theoretically, demonstrating the 'desirable' performance in 90 positive participants would reduce that probability to below 5%. A marked reduction in the probability of failure to hit 'desirable' specificity occurred between samples of 100 (19.1-21.5%) and 160 (4.3-4.8%) negative participants. There was little further improvement above sample sizes of 160 negative participants. CONCLUSION: Based on imprecision alone, small evaluation studies can lead to the acceptance of diagnostic tests which are likely to fail to meet performance targets when deployed. There is diminished return on uncertainty surrounding an accuracy estimate above a total sample size of 250 (90 positive and 160 negative).

Pharmacogenetics to Avoid Loss of Hearing (PALOH) trial: a protocol for a prospective observational implementation trial.

INTRODUCTION: In conjunction with a beta-lactam, aminoglycosides are the first-choice antibiotic for empirical treatment of sepsis in the neonatal period. The m.1555A>G variant predisposes to ototoxicity after aminoglycoside administration and has a prevalence of 1 in 500. Current genetic testing can take over 24 hours, an unacceptable delay in the acute setting. This prospective-observational trial will implement a rapid point of care test (POCT), facilitating tailored antibiotic prescribing to avoid hearing loss. METHODS AND ANALYSIS: The genedrive POCT can detect the m.1555A>G variant in 26 min from buccal swab. This system will be integrated into the clinical pathways at two large UK neonatal centres over a minimum 6-month period. The primary outcome is the number of neonates successfully tested for the variant out of all babies prescribed antibiotics. As a secondary outcome, clinical timings will be compared with data collected prior to implementation, measuring the impact on routine practice. ETHICS AND DISSEMINATION: Approval for the trial was granted by the Research Ethics Committee (REC) and Human Research Authority in August 2019. Results will be published in full on completion of the study. TRIAL REGISTRATION NUMBER: ISRCTN13704894. PROTOCOL VERSION: V 1.3.

A Nonadaptive Combinatorial Group Testing Strategy to Facilitate Health Care Worker Screening during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Outbreak.

Routine testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in health care workers (HCWs) is critical. Group testing strategies to increase capacity facilitate mass population testing but do not prioritize turnaround time, an important consideration for HCW screening. We propose a nonadaptive combinatorial (NAC) group testing strategy to increase throughput while facilitating rapid turnaround. NAC matrices were constructed for sample sizes of 700, 350, and 250. Matrix performance was tested by simulation under different SARS-CoV-2 prevalence scenarios of 0.1% to 10%. NAC matrices were compared versus Dorfman sequential (DS) group testing approaches. NAC matrices performed well at low prevalence levels, with an average of 97% of samples resolved after a single round of testing via the n = 700 matrix at a prevalence of 1%. In simulations of low to medium (0.1% to 3%) prevalence, all NAC matrices were superior to the DS strategy, measured by fewer repeated tests required. At very high prevalence levels (10%), the DS matrix was marginally superior, although both group testing approaches performed poorly at high prevalence levels. This strategy maximizes the proportion of samples resolved after a single round of testing, allowing prompt return of results to HCWs. This methodology may allow laboratories to adapt their testing scheme based on required throughput and the current population prevalence, facilitating a data-driven testing strategy.

Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission.

Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting.

Covid‐19 and Global Food Security

Covid-19 has major implications for global food security. The virus itself and the policy reactions have triggered a massive recession and major disruptions in food value chains. The combination of both has been dramatic for the food and nutrition security of billions of poor people around the world. The impacts are heterogeneous, depending on the nature of the commodity, the resource-intensity of the food systems, and the level of economic development. Covid-19 affects the food security and nutrition of poor people more strongly than that of richer people. Women, children and migrants are particularly affected. It is important to balance movement control and other social distancing measures with policy initiatives to improve the food and nutrition security and livelihoods of vulnerable groups. A crucial issue moving forward is to make food supply chains, and food systems generally, more resilient for the future. While many food systems have been significantly disrupted, others have been more resilient, with food supplies relatively unaffected. Innovations are helping to overcome obstacles and make food supply chains more resilient for the future. Overall, the insights and lessons from Covid-19 should help to design better policies and build more resilient and inclusive food systems for the future.

Sociodemographic variables as predictors of adverse outcome in SARS-CoV-2 infection: an Irish hospital experience.

INTRODUCTION: Our hospital found itself at the epicentre of the Irish COVID-19 pandemic. We describe the organisational challenges faced in managing the surge and identified risk factors for mortality and ICU admission among hospitalised SARS-CoV-2-infected patients. METHODS: All hospitalised SARS-CoV-2 patients diagnosed between March 13 and May 1, 2020, were included. Demographic, referral, deprivation, ethnicity and clinical data were recorded. Multivariable regression, including age-adjusted hazard ratios (HR (95% CI), was used to explore risk factors associated with adverse outcomes. RESULTS: Of 257 inpatients, 174 were discharged (68%) and 39 died (15%) in hospital. Two hundred three (79%) patients presented from the community, 34 (13%) from care homes and 20 (8%) were existing inpatients. Forty-five percent of community patients were of a non-Irish White or Black, Asian or minority ethnic (BAME) population, including 34 Roma (13%) compared to 3% of care home and 5% of existing inpatients, (p < 0.001). Twenty-two patients were healthcare workers (9%). Of 31 patients (12%) requiring ICU admission, 18 were discharged (58%) and 7 died (23%). Being overweight/obese HR (95% CI) 3.09 (1.32, 7.23), p = 0.009; a care home resident 2.68 (1.24, 5.6), p = 0.012; socioeconomically deprived 1.05 (1.01, 1.09), p = 0.012; and older 1.04 (1.01, 1.06), p = 0.002 were significantly associated with death. Non-Irish White or BAME were not significantly associated with death 1.31 (0.28, 6.22), p = 0.63 but were significantly associated with ICU admission 4.38 (1.38, 14.2), p = 0.014 as was being overweight/obese 2.37 (1.37, 6.83), p = 0.01. CONCLUSION: The COVID-19 pandemic posed unprecedented organisational issues for our hospital resulting in the greatest surge in ICU capacity above baseline of any Irish hospital. Being overweight/obese, a care home resident, socioeconomically deprived and older were significantly associated with death, while ethnicity and being overweight/obese were significantly associated with ICU admission.

Refusal of viral testing during the SARS-CoV-2 pandemic.

Widespread testing for the respiratory syndrome coronavirus-2 (SARS-CoV-2) will represent an important part of any strategy designed to safely reopen societies from lockdown. Healthcare settings have the potential to become reservoirs of infectivity, and therefore many hospital trusts are beginning to carry out routine screening of staff and patients. This could promote the effective cohorting of patients and reduce the rate of nosocomial infection. However, for various reasons, some individuals may refuse this testing. Here we highlight this as an emergent ethicolegal issue which we expect to become increasingly relevant as testing becomes ubiquitous. We explore this position from an ethical and legal perspective, determining whether refusal of testing is acceptable under UK law. Individual patients refusing testing could undermine a hospital's testing strategy; therefore clinicians and policy makers must prospectively determine the best course of action if this were to occur.