A Bayesian spatio-temporal study of meteorological factors affecting the spread of COVID-19

The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as the flu it's suggested that COVID-19 may become seasonal as immunity grows. Yet the effects of meteorological conditions on the spread of COVID-19 are poorly understood with previous studies producing contrasting results, due at least in part to limited and inconsistent study designs. This study investigates the effect of meteorological conditions on COVID-19 infections in England using a spatio-temporal model applied to case counts during the initial England lockdown. By modelling spatial and temporal effects to account for the nature of a human transmissible virus the model isolates meteorological effects. Inference based on 95% highest posterior density intervals shows humidity is negatively associated with COVID-19 spread. The lack of evidence for other weather factors affecting COVID-19 transmission shows care should be taken with respect to seasonality when designing COVID-19 policies and public communications.Comment: 23 pages, 13 figures (inclusive of references and appendix

A Bayesian spatio-temporal study of the association between meteorological factors and the spread of COVID-19

BACKGROUND: The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population, transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as influenza some authors have suggested COVID-19 may become seasonal as immunity grows. Despite this, the effects of meteorological conditions on the spread of COVID-19 are poorly understood. Previous studies have produced contrasting results, due in part to limited and inconsistent study designs. METHODS: This study investigates the effects of meteorological conditions on COVID-19 infections in England using a Bayesian conditional auto-regressive spatio-temporal model. Our data consists of daily case counts from local authorities in England during the first lockdown from March-May 2020. During this period, legal restrictions limiting human interaction remained consistent, minimising the impact of changes in human interaction. We introduce a lag from weather conditions to daily cases to accommodate an incubation period and delays in obtaining test results. By modelling spatio-temporal random effects we account for the nature of a human transmissible virus, allowing the model to isolate meteorological effects. RESULTS: Our analysis considers cases across England's 312 local authorities for a 55-day period. We find relative humidity is negatively associated with COVID-19 cases, with a 1% increase in relative humidity corresponding to a reduction in relative risk of 0.2% [95% highest posterior density (HPD): 0.1-0.3%]. However, we find no evidence for temperature, wind speed, precipitation or solar radiation being associated with COVID-19 spread. The inclusion of weekdays highlights systematic under reporting of cases on weekends with between 27.2-43.7% fewer cases reported on Saturdays and 26.3-44.8% fewer cases on Sundays respectively (based on 95% HPDs). CONCLUSION: By applying a Bayesian conditional auto-regressive model to COVID-19 case data we capture the underlying spatio-temporal trends present in the data. This enables us to isolate the main meteorological effects and make robust claims about the association of weather variables to COVID-19 incidence. Overall, we find no strong association between meteorological factors and COVID-19 transmission

Composite endpoints for malaria case-management: not simplifying the picture?

Rapid diagnostic tests (RDTs) for infection with Plasmodium spp. offer two main potential advantages related to malaria treatment: 1) ensuring that individuals with malaria are promptly treated with an effective artemisinin-based combination therapy, and 2) ensuring that individuals without malaria do not receive an anti-malarial they do not need (and instead receive a more appropriate treatment). Some studies of the impact of RDTs on malaria case management have combined these two different successes into a binary outcome describing 'correct management'. However combining correct management of positives and negatives into a single summary measure can be misleading. The problems, which are analogous to those encountered in the evaluation of diagnostic tests, can largely be avoided if data for patients with and without malaria are presented and analysed separately. Where a combined metric is necessary, then one of the established approaches to summarise the performance of diagnostic tests could be considered, although these are not without their limitations. Two graphical approaches to help understand case management performance are illustrated

Linear mixed models to handle missing at random data in trial-based economic evaluations

Trial-based cost-effectiveness analyses (CEAs) are an important source of evidence in the assessment of health interventions. In these studies, cost and effectiveness outcomes are commonly measured at multiple time points, but some observations may be missing. Restricting the analysis to the participants with complete data can lead to biased and inefficient estimates. Methods, such as multiple imputation, have been recommended as they make better use of the data available and are valid under less restrictive Missing At Random (MAR) assumption. Linear mixed effects models (LMMs) offer a simple alternative to handle missing data under MAR without requiring imputations, and have not been very well explored in the CEA context. In this manuscript, we aim to familiarize readers with LMMs and demonstrate their implementation in CEA. We illustrate the approach on a randomized trial of antidepressants, and provide the implementation code in R and Stata. We hope that the more familiar statistical framework associated with LMMs, compared to other missing data approaches, will encourage their implementation and move practitioners away from inadequate methods

Monitoring patient care through health facility exit interviews: an assessment of the Hawthorne effect in a trial of adherence to malaria treatment guidelines in Tanzania.

BACKGROUND: Survey of patients exiting health facilities is a common way to assess consultation practices. It is, however, unclear to what extent health professionals may change their practices when they are aware of such interviews taking place, possibly paying more attention to following recommended practices. This so-called Hawthorne effect could have important consequences for interpreting research and programme monitoring, but has rarely been assessed. METHODS: A three-arm cluster-randomised trial of interventions to improve adherence to guidelines for the use of anti-malarial drugs was conducted in Tanzania. Patient interviews were conducted outside health facilities on two randomly-selected days per week. Health workers also routinely documented consultations in their ledgers. The Hawthorne effect was investigated by comparing routine data according to whether exit interviews had been conducted on three key indicators of malaria care. Adjusted logistic mixed-effects models were used, taking into account the dependencies within health facilities and calendar days. RESULTS: Routine data were collected on 19,579 consultations in 18 facilities. The odds of having a malaria rapid diagnostic test (RDT) result reported were 11 % higher on days when exit surveys were conducted (adjusted odds ratio 95 % CI: 0.98-1.26, p = 0.097), 17 % lower for prescribing an anti-malarial drug to patients with a negative RDT result (0.56-1.23, p = 0.343), and 27 % lower for prescribing an anti-malarial when no RDT result was reported (0.53-1.00, p = 0.052). The effect varied with time, with a U-shaped association over the study period (p < 0.001). We also observed a higher number of consultations recorded on days when exit-interviews were conducted (adjusted mean difference = 2.03, p < 0.001). CONCLUSIONS: Although modest, there was some suggestion of better practice by health professionals on days when exit interviews were conducted. Researchers should be aware of the potential Hawthorne effect, and take into account assessment methods when generalising findings to the 'real word' setting. This effect is, however, likely to be context dependent, and further controlled evaluation across different settings should be conducted. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01292707 . Registered on 29th January 2011

A randomised controlled trial of an intervention delivered by app instant messaging to increase the acceptability of effective contraception among young people in Tajikistan: study protocol.

INTRODUCTION: Women in lower income countries experience unintended pregnancies at a higher rate compared with women in higher income countries. Unintended pregnancy is associated with numerous poorer health outcomes for both women and their children. In Tajikistan, an estimated 26% of married individuals aged 15-24 years have an unmet need for contraception. The strong cultural value placed on childbearing and oppositional attitudes towards contraception are major barriers to contraceptive uptake in the country.Mobile phone ownership is widespread in Tajikistan. The option of receiving reproductive health support on your personal phone may be an appealing alternative to attending a clinic, particularly for young people. The London School of Hygiene & Tropical Medicine and the Tajik Family Planning Association have partnered to develop and evaluate a contraceptive behavioural intervention delivered by mobile phone. The intervention was developed in 2015-2016 guided by behavioural science. It consists of short instant messages sent through an app over 4 months, contains information about contraception and behaviour change methods. METHODS AND ANALYSIS: This randomised controlled trial is designed to evaluate the effect of the intervention on self-reported acceptability of effective contraception at 4 months. 570 men and women aged 16-24 years will be allocated with a ratio of 1:1 to receive the intervention messages or the control messages about trial participation. The messages will be sent through the Tajik Family Planning Association's 'healthy lifestyles' app, which contains basic information about contraception. ETHICS AND DISSEMINATION: The trial was granted ethical approval by the London School of Hygiene & Tropical Medicine Interventions Research Ethics Committee on 16 May 2016 and by the Tajik National Scientific and Research Centre on Paediatrics and Child Surgery on 15 April 2016. The results of the trial will be submitted for publication in peer-reviewed academic journals and disseminated to study stakeholders. TRIAL REGISTRATION NUMBER: Clinicaltrial.gov NCT02905513. DATE OF REGISTRATION: 14 September 2016. WHO TRIAL REGISTRATION DATASET: http://apps.who.int/trialsearch/Trial2.aspx?TrialID=NCT02905513

Drug therapy for delirium in terminally ill adult patients.

BACKGROUND: Delirium is a syndrome characterised by a disturbance of consciousness (often fluctuating), cognition and perception. In terminally ill patients it is one of the most common causes of admission to clinical care. Delirium may arise from any number of causes and treatment should be directed at addressing these causes rather than the symptom cluster. In cases where this is not possible, or treatment does not prove successful, the use of drug therapy to manage the symptoms may become necessary. This is an update of the review published on 'Drug therapy for delirium in terminally ill adult patients' in The Cochrane Library 2004, Issue 2 ( Jackson 2004). OBJECTIVES: To evaluate the effectiveness of drug therapies to treat delirium in adult patients in the terminal phase of a disease. SEARCH METHODS: We searched the following sources: CENTRAL (The Cochrane Library 2012, Issue 7), MEDLINE (1966 to 2012), EMBASE (1980 to 2012), CINAHL (1982 to 2012) and PSYCINFO (1990 to 2012). SELECTION CRITERIA: Prospective trials with or without randomisation or blinding involving the use of drug therapies for the treatment of delirium in adult patients in the terminal phase of a disease. DATA COLLECTION AND ANALYSIS: Two authors independently assessed trial quality using standardised methods and extracted trial data. We collected outcomes related to efficacy and adverse effects. MAIN RESULTS: One trial met the criteria for inclusion. In the 2012 update search we retrieved 3066 citations but identified no new trials. The included trial evaluated 30 hospitalised AIDS patients receiving one of three agents: chlorpromazine, haloperidol and lorazepam. The trial under-reported key methodological features. It found overall that patients in the chlorpromazine group and those in the haloperidol group had fewer symptoms of delirium at follow-up (to below the diagnostic threshold using the Diagnostic and Statistical Manual of Mental Disorders (DSM-III) and that both were equally effective (at two days mean difference (MD) 0.37; 95% confidence interval (CI) -4.58 to 5.32; between two and six days MD -0.21; 95% CI -5.35 to 4.93). Chlorpromazine and haloperidol were found to be no different in improving cognitive status in the short term (at 48 hours) but at subsequent follow-up cognitive status was reduced in those taking chlorpromazine. Improvements from baseline to day two for patients randomised to lorazepam were not apparent. All patients on lorazepam (n = 6) developed adverse effects, including oversedation and increased confusion, leading to trial drug discontinuation. AUTHORS' CONCLUSIONS: There remains insufficient evidence to draw conclusions about the role of drug therapy in the treatment of delirium in terminally ill patients. Thus, practitioners should continue to follow current clinical guidelines. Further research is essential

Cluster randomized trials with a small number of clusters: which analyses should be used?

BACKGROUND: Cluster randomized trials (CRTs) are increasingly used to assess the effectiveness of health interventions. Three main analysis approaches are: cluster-level analyses, mixed-models and generalized estimating equations (GEEs). Mixed models and GEEs can lead to inflated type I error rates with a small number of clusters, and numerous small-sample corrections have been proposed to circumvent this problem. However, the impact of these methods on power is still unclear. METHODS: We performed a simulation study to assess the performance of 12 analysis approaches for CRTs with a continuous outcome and 40 or fewer clusters. These included weighted and unweighted cluster-level analyses, mixed-effects models with different degree-of-freedom corrections, and GEEs with and without a small-sample correction. We assessed these approaches across different values of the intraclass correlation coefficient (ICC), numbers of clusters and variability in cluster sizes. RESULTS: Unweighted and variance-weighted cluster-level analysis, mixed models with degree-of-freedom corrections, and GEE with a small-sample correction all maintained the type I error rate at or below 5% across most scenarios, whereas uncorrected approaches lead to inflated type I error rates. However, these analyses had low power (below 50% in some scenarios) when fewer than 20 clusters were randomized, with none reaching the expected 80% power. CONCLUSIONS: Small-sample corrections or variance-weighted cluster-level analyses are recommended for the analysis of continuous outcomes in CRTs with a small number of clusters. The use of these corrections should be incorporated into the sample size calculation to prevent studies from being underpowered

School violence, depression symptoms, and school climate: a cross-sectional study of Congolese and Burundian refugee children

Forcibly displaced children are at increased risk of violence and mental health disorders. In refugee contexts, schools are generally perceived as protective environments where children can build a sense of belonging and recover from trauma. Evidence shows that positive school climates can support student skills development and socio-emotional wellbeing and protect them against a host of adverse outcomes. However, schools are also places where children may experience violence, from both teachers and peers. Prevalence estimates of violence against children in humanitarian settings are scarce and evidence on the relationship between school climate and student outcomes in these contexts is non-existent. The aim of the study is to estimate the prevalence of school-based violence against children and to explore the association between perceptions of school climate and students’ experiences and use of violence and their depression symptoms. We relied on data from a cross-sectional survey of students and teachers in all primary and secondary schools in Nyarugusu Refugee Camp in Tanzania, conducted as part of a cluster randomised controlled trial, to compute prevalence estimates and used mixed logistic regression analysis to assess the association between school climate and students’ outcomes. We found that students in Nyarugusu experienced high levels of violence from both peers and teachers in both primary and secondary schools in the camp, with little difference between boys and girls. Nearly one in ten students screened positive for symptoms of depression. We found that opportunities for students and teachers to be involved in decision-making were associated with higher odds of violent discipline and teachers’ self-efficacy was a significant protective factor against student depression symptoms. However, generally, school-level perceptions of school climate were not associated with student outcomes after adjusting for potential confounders. Our findings suggest that interventions to prevent and respond to teacher and peer violence in schools and to support students’ mental health are urgently needed. Our results challenge the assumption that education environments are inherently protective for children and call for further investigation of norms around violence among students and teachers to better understand the role of school climate in refugee settings