Emily Nightingale

As tuberculosis (TB) incidence declines, transmission becomes increasingly concentrated in vulnerable populations and neighbourhoods. There is an urgent need for affordable surveillance strategies to monitor trends, identify high-risk groups and target interventions. TB disease prevalence surveys are no longer cost-effective in monitoring epidemiological trends as countries target TB elimination, while passive surveillance methodologies such as case-notification rates (CNRs) are biased by healthcare access disparities. Mycobacterium tuberculosis (Mtb) immunoreactivity surveys indirectly measure transmission and therefore undiagnosed infectious TB, and may provide valuable information to TB programmes globally. We conducted a pragmatic hybrid clinic- and household-based cross-sectional interferon-gamma release assay (IGRA) survey in healthy children aged 1–4 years in 33 high-burden neighbourhoods Blantyre, Malawi. Participants were recruited using novel convenience sampling in health facilities, alongside random household sampling guided by satellite imagery, and tested for Mtb immunoreactivity using QFT-Plus IGRA. We constructed hierarchical Bayesian logistic regression models for IGRA positivity, with neighbourhood-level random effects. Of 1,545 participants, 102 (6.6%) had a positive IGRA: an annual risk of Mtb infection (ARTI) of 2.7% (95% CrI 2.2-3.2%). Immunoreactivity was higher in the poorest third of households (8.7% vs 4.9%; adjusted odds ratio: 1.88, 95% CrI 1.08-3.01) compared to the richest, but was not associated with HIV exposure, malnutrition or reported household TB exposure. There was substantial between-neighbourhood heterogeneity (ARTI range 1.1-4.1%). There was no association between neighbourhood-level TB case notifications and ARTI. Measuring Mtb immunoreactivity in young children, using innovative recruitment strategies, revealed a high burden of immunoreactivity suggestive of recent TB transmission. Children in the poorest households were at highest risk, highlighting the importance of social and economic inequity in driving the TB epidemic. Case notification rates may not reflect the areas with the highest transmission, and Mtb immunoreactivity surveillance may support identification of high-risk populations, monitoring of trends and targeting of public health interventions.

A fundamental question in the global commitment to polio eradication is how long a period of absence would be consistent with regional elimination, and the safe withdrawal of the oral polio vaccine is contingent on the answer. We present a statistical framework to model the time-varying sensitivity of two key components of polio surveillance - environmental sampling and clinical cases of acute flaccid paralysis - for detecting infection on a monthly basis at the local government authority level. We use this to estimate the probability of freedom from infection (FFI) at a critical prevalence level that is consistent with interruption of transmission, given the absence of virus in collected samples. We validated this framework against two periods of poliovirus absence in Nigeria (2014–2016 and 2016–2020). Our model highlights substantial heterogeneity in surveillance sensitivity over time and space and, given this, concluded an 85% probability (95% uncertainty interval: 77.1-90.0%) of the country being free from WPV1 infection after 23 months without detection from July 2014. Detection of WPV1 in July 2016 demonstrated that circulation had indeed persisted during this time. In contrast, we conclude a probability of 98% (97.5-98.5%) by the time elimination of the serotype was officially declared in 2020. The inferred probability of FFI during both time periods was found to be consistent with the retrospectively known status of regional elimination. This supports the validity of applying this framework prospectively to inform the certification of wild poliovirus elimination from remaining endemic regions, and to determine the resolution of cVDPV2 outbreaks.

We reflect on the sustainability of modelling infectious disease outbreaks from the perspective of modelling as a field of practice. We formed a community of practice among UK infectious disease modellers who had contributed to the UK COVID-19 response. We previously used a participatory workshop approach to highlight issues in the infrastructure and incentives for outbreak modelling, and synthesized our experience into a set of 12 specific recommendations. Here, we track changes in the field of infectious disease modelling 1 year later, collecting the quantitative and qualitative views of change among 14 participants. We found participants continued to highlight a lack of ongoing, sufficient or appropriate action to develop outbreak modelling capacity in the UK, while positively noting collaborations among public health facing institutions. We emphasize the under-prioritization of funding for outbreak modelling outside of emergency response periods, and the continuation of unsustainable working practices. Correcting this is crucial to supporting evidence-based public health policy for outbreak preparedness and response.

Background: Visceral leishmaniasis (VL) is a debilitating and—without treatment—fatal parasitic disease which burdens the most impoverished communities in northeastern India. Control and ultimately, elimination of VL depends heavily on prompt case detection. However, a proportion of VL cases remain undiagnosed many months after symptom onset. Delay to diagnosis increases the chance of onward transmission, and poses a risk of resurgence in populations with waning immunity. We analysed the spatial variation of delayed diagnosis of VL in Bihar, India and aimed to understand the potential driving factors of these delays. Methods: The spatial distribution of time to diagnosis was explored using a Bayesian hierarchical model fit to 4270 geo-located cases notified between January 2018 and July 2019 through routine surveillance. Days between symptoms meeting clinical criteria (14-day fever) and diagnosis were assumed to be Poisson-distributed, adjusting for individual- and village-level characteristics. Residual variance was modelled with an explicit spatial structure. Cumulative delays were estimated under different scenarios of active case detection coverage. Results: The 4270 cases analysed were found to be prone to excessive delays in areas outside existing endemic ‘hot spots’. After accounting for differences associated with age, HIV status and mode of detection (active versus passive surveillance), cases diagnosed within recently affected (≥ 1 case reported in the previous year) blocks and villages experienced shorter delays on average (by 13% [2.9–21.7%] (95% credible interval) and 7% [1.3–13.1%], respectively) than those in non-recently-affected areas. Conclusions: Delays to VL diagnosis when incidence is low could influence whether transmission of the disease could be interrupted or resurges. Prioritising and narrowing surveillance to high-burden areas may increase the likelihood of excessive delays in diagnosis in peripheral areas. Active surveillance driven by observed incidence may lead to missing the risk posed by as-yet-undiagnosed cases in low-endemic areas, and such surveillance could be insufficient for achieving and sustaining elimination.

Substantial evidence demonstrates that men have a higher prevalence of tuberculosis (TB) and decreased use of TB services compared to women. Gender roles and norms contribute to these disparities by influencing social and structural determinants, as well as individual behaviours. In this analysis, we investigated attitudes towards gender equitable norms and TB testing behaviours amongst Malawian men and women participating in a prevalence survey conducted before a community-based TB active case finding trial in Blantyre. Perceptions of gender norms were captured through a modified version of the Gender Equitable Men Scale (GEMS). Gender inequitable views were prevalent among both men (56.1%) and women (55.8%). The association between a composite GEMS score and TB testing history was modelled using logistic regression, accounting for various sociodemographic covariates (age, sex, wealth quantile, education, and HIV status) (OR = 1.12, 95% CI: 0.88-1.42, p=0.373). Bivariate analysis demonstrated no notable confounding by any covariates and no strong effect modification. While GEMS score had no association with TB testing history among women, men with higher GEMS scores (less gender-equitable views) were more likely to have been tested for TB across age groups. These findings provide a basis for future investigation into the patterns and motives TB behaviours, particularly in older men. Tailored public health strategies may then be implemented to address this important population.

A fundamental question in the global commitment to polio eradication is how long a period of absence would be consistent with regional elimination, and the safe withdrawal of the oral polio vaccine is contingent on the answer. We present a statistical framework to model the time-varying sensitivity of two key components of polio surveillance - environmental sampling and clinical cases of acute flaccid paralysis - for detecting infection on a monthly basis at the local government authority level. We use this to estimate the probability of freedom from infection (FFI) at a critical prevalence level that is consistent with interruption of transmission, given the absence of virus in collected samples. We validated this framework against two periods of poliovirus absence in Nigeria (2014-2016 and 2016-2020). Our model highlights substantial heterogeneity in surveillance sensitivity over time and space and, given this, concluded an 85% probability (95% uncertainty interval: 77.1-90.2%) of the country being free from WPV1 infection after 23 months without detection from July 2014. Detection of WPV1 in July 2016 demonstrated that circulation had indeed persisted during this time. In contrast, we conclude a probability of 98% (97.9-98.7%) by the time elimination of the serotype was officially declared in 2020. The inferred probability of FFI during both time periods was found to be consistent with the retrospectively known status of regional elimination. This supports the validity of applying this framework prospectively to inform the certification of wild poliovirus elimination from remaining endemic regions, and to determine the resolution of cVDPV2 outbreaks.

On March 11th 2020, the World Health Organization characterised COVID-19 as a pandemic. Responses to containing the spread of the virus have relied heavily on policies involving restricting contact between people. Evolving policies regarding shielding and individual choices about restricting social contact will rely heavily on perceived risk of poor outcomes from COVID-19. In order to make informed decisions, both individual and collective, good predictive models are required. For outcomes related to an infectious disease, the performance of any risk prediction model will depend heavily on the underlying prevalence of infection in the population of interest. Incorporating measures of how this changes over time may result in important improvements in prediction model performance. This protocol reports details of a planned study to explore the extent to which incorporating time-varying measures of infection burden over time improves the quality of risk prediction models for COVID-19 death in a large population of adult patients in England. To achieve this aim, we will compare the performance of different modelling approaches to risk prediction, including static cohort approaches typically used in chronic disease settings and landmarking approaches incorporating time-varying measures of infection prevalence and policy change, using COVID-19 related deaths data linked to longitudinal primary care electronic health records data within the OpenSAFELY secure analytics platform.

Introduction: Decentralized COVID-19 testing with antigen rapid diagnostic tests (Ag-RDT) is recommended by the Nigerian Centre for Disease Control for community-level services. These services have been provided in Primary Healthcare Centers, Community Pharmacies, and licensed “Patent Medicine Stores” that serve the least affluent communities. To support quality assurance, we applied an adapted version of SPI-RT (Stepwise Process for Improving the Quality of HIV Rapid and Recency Testing) to sites providing COVID-19-RDTs in Federal Capital Territory of Nigeria. Methods: Between September 2022 and February 2023 community healthcare facilities (48 Community Pharmacies, 21 Patent Medicine Stores, 79 Primary Health Centers) were evaluated using Stepwise Process for Improving the Quality of SARS-CoV-2 Antigen Rapid Diagnostic Testing (SPI-RT) Checklist, tailored to the local implementation context. Evaluated domains included service quality, documents and records, personnel training and certification, safety, physical infrastructure, pre-testing phase, testing phase, and post-testing phase. Each facility received an overall score, expressed as a percentage indicating their performance level. Results: 41/79 (52%) of Primary Health Centers scored at least 90% for service quality, as did 19/48 (40%) of pharmacies, with only 1/21 (4.8%) Patent Medicine Store. Apart from personnel training and certification, Primary Health Centers scored highest across most domains of service quality, followed by Community Pharmacies. The lowest median score in any domain was in the Patent Medicine Stores on testing and safety at 60% for both post-testing phase and safety. Conclusion: Primary Healthcare Centers and Community Pharmacies can provide quality decentralized testing for COVID-19. Patent Medicine Stores may need additional support including monitoring and quality improvement initiatives to ensure the provision of high-quality decentralized COVID-19 rapid testing services.

Background: As cases of visceral leishmaniasis (VL) in India dwindle, there is motivation to monitor elimination progress on a finer geographic scale than sub-district (block). Low-incidence projections across geographically- and demographically- heterogeneous communities are difficult to act upon, and equitable elimination cannot be achieved if local pockets of incidence are overlooked. However, maintaining consistent surveillance at this scale is resource-intensive and not sustainable in the long-term. Methods: We analysed VL incidence across 45,000 villages in Bihar state, exploring spatial autocorrelation and associations with local environmental conditions in order to assess the feasibility of inference at this scale. We evaluated a statistical disaggregation approach to infer finer spatial variation from routinely-collected, block-level data, validating against observed village-level incidence. Results: This disaggregation approach does not estimate village-level incidence more accurately than a baseline assumption of block-homogeneity. Spatial auto-correlation is evident on a block-level but weak between neighbouring villages within the same block, possibly suggesting that longer-range transmission (e.g., due to population movement) may be an important contributor to village-level heterogeneity. Conclusions: Increasing the range of reactive interventions to neighbouring villages may not improve their efficacy in suppressing transmission, but maintaining surveillance and diagnostic capacity in areas distant from recently observed cases - particularly along routes of population movement from endemic regions - could reduce reintroduction risk in currently unaffected villages. The reactive, spatially-targeted approach to VL surveillance limits interpretability of data observed at the village level, and hence the feasibility of routinely drawing and validating inference at this scale.