Background Understanding human movement patterns and their association with risk factors for the acquisition and transmission of pathogens can inform guidance for disease control. In Vietnam, acute encephalitis syndrome (AES) has a wide-ranging etiology; however, it is hypothesized that many causes are due to vector-borne diseases. Methods We undertook a study in Ha Nam province, northern Vietnam, to determine the acceptability and feasibility of using i-gotU GT-120 GPS devices to understand the mobility patterns of healthy residents and evaluate the time spent in areas deemed to be at risk of bites from vectors. Focus group discussions (FGDs) were carried out to understand the knowledge and perceptions of GPS devices. Following this, 48 participants wore a GPS device for eight 72-hour periods over a year from which movement data and feedback were obtained. Results Concerns about the GPS included risks to privacy and health, and losing the device. However, compliance was good with 80,831 unique coordinates obtained and participants carrying the devices for 13,411 km over the study period. All groups of participants (adults and children, and those from urban and rural settings) travelled outside of Ha Nam province however, most spent the greatest proportion of time in areas with a low normalized difference vegetation index (NDVI) which was associated with a decreased risk of bites from vectors. Conclusions Our study demonstrates that the use of GPS devices in this setting was a feasible method for collecting data on movement patterns. However, for future studies, given the cost and logistics of using the GPS devices, we recommend exploring methods which allow for a larger sample size.

Central nervous system (CNS) infections are an important cause of morbidity and mortality in Vietnam, with many studies conducted to determine the aetiology. However, the cause remains unknown in a large proportion of cases. Although a systematic review of the aetiologies of CNS infections was conducted in the Mekong region, there are no known published reviews of the studies specifically in Vietnam. Here, we review the cause of CNS infections in Vietnam while also considering the potential aetiologies where a cause was not identified, based on the literature from the region. In particular, we focus on the most common pathogens in adults and children including Streptococcus suis which is associated with the consumption of raw pig products, and Japanese encephalitis virus, a mosquito-borne pathogen. We also discuss pathogens less commonly known to cause CNS infections in Vietnam but have been detected in neighbouring countries such as Orientia tsutsugamushi, Rickettsia typhi and Leptospira species and how these may contribute to the unknown causes in Vietnam. We anticipate that this review may help guide future public health measures to reduce the burden of known pathogens and broaden testing to help identify additional aetiologies.

BackgroundConflict is known to impact maternal and neonatal health in Eastern Democratic Republic of the Congo (DRC), an area of longstanding insecurity. We conducted a systematic review on pregnancy and neonatal outcomes in this region to provide a comprehensive overview of maternal and neonatal outcomes over a 20-year period.MethodsWe systematically searched databases, such as Medline, EMBASE, Global Health, ClinicalTrials.gov and the Cochrane Library, along with grey literature, for articles published between 2001 and 2021. These articles provided quantitative data on selected pregnancy and neonatal outcomes in the provinces of Ituri, Maniema and North and South Kivu, Eastern DRC. We conducted a descriptive analysis, combining results from different data sources and comparing incidence of outcomes in North Kivu with those in other provinces in Eastern DRC.ResultsA total of 1,065 abstracts from peer-reviewed publications and 196 articles from the grey literature were screened, resulting in the inclusion of 14 scientific articles in the review. The most frequently reported pregnancy complications were caesarean sections (11.6%–48.3% of deliveries) and miscarriage (1.2%–30.0% of deliveries). The most common neonatal outcomes were low birth weight (3.8%–21.9% of live births), preterm birth (0.9%–74.0%) and neonatal death (0.2%–43.3%).ConclusionOur review provides data on pregnancy and neonatal outcomes in Eastern DRC, which will be valuable for future studies. Despite the area's ongoing armed conflict, the percentages of complications we noted in Eastern DRC are comparable with those observed in other countries in the region.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=262553, PROSPERO (CRD42021262553).

During the 2018–2020 Ebola virus disease outbreak in Democratic Republic of the Congo, a phase 3 trial of the Ad26.ZEBOV, MVA-BN-Filo Ebola vaccine (DRC-EB-001) commenced in Goma, with participants being offered the two-dose regimen given 56 days apart. Suspension of trial activities in 2020 due to the COVID-19 pandemic led to some participants receiving a late dose 2 outside the planned interval. Blood samples were collected from adults, adolescents, and children prior to their delayed dose 2 vaccination and 21 days after, and tested for IgG binding antibodies against Ebola virus glycoprotein using the Filovirus Animal Nonclinical Group (FANG) ELISA. Results from 133 participants showed a median two-dose interval of 9.3 months. The pre-dose 2 antibody geometric mean concentration (GMC) was 217 ELISA Units (EU)/mL (95% CI 157; 301) in adults, 378 EU/mL (281; 510) in adolescents, and 558 EU/mL (471; 661) in children. At 21 days post-dose 2, the GMC increased to 22,194 EU/mL (16,726; 29,449) in adults, 37,896 EU/mL (29,985; 47,893) in adolescents, and 34,652 EU/mL (27,906; 43,028) in children. Participants receiving a delayed dose 2 had a higher GMC at 21 days post-dose 2 than those who received a standard 56-day regimen in other African trials, but similar to those who received the regimen with an extended interval.

During the 2018–2020 Ebola virus disease (EVD) outbreak, residents in Goma, Democratic Republic of the Congo, were offered a two-dose prophylactic EVD vaccine. This was the first study to evaluate the safety of this vaccine in pregnant women. Adults, including pregnant women, and children aged ≥1 year old were offered the Ad26.ZEBOV (day 0; dose 1), MVA-BN-Filo (day 56; dose 2) EVD vaccine through an open-label clinical trial. In total, 20,408 participants, including 6635 (32.5%) children, received dose 1. Fewer than 1% of non-pregnant participants experienced a serious adverse event (SAE) following dose 1; one SAE was possibly related to the Ad26.ZEBOV vaccine. Of the 1221 pregnant women, 371 (30.4%) experienced an SAE, with caesarean section being the most common event. No SAEs in pregnant women were considered related to vaccination. Of 1169 pregnancies with a known outcome, 55 (4.7%) ended in a miscarriage, and 30 (2.6%) in a stillbirth. Eleven (1.0%) live births ended in early neonatal death, and five (0.4%) had a congenital abnormality. Overall, 188/891 (21.1%) were preterm births and 79/1032 (7.6%) had low birth weight. The uptake of the two-dose regimen was high: 15,328/20,408 (75.1%). The vaccine regimen was well-tolerated among the study participants, including pregnant women, although further data, ideally from controlled trials, are needed in this crucial group.

BackgroundGlobally, since 1 January 2020 and as of 24 January 2023, there have been over 664 million cases of COVID-19 and over 6.7 million deaths reported to WHO. WHO developed an evidence-based alert system, assessing public health risk on a weekly basis in 237 countries, territories and areas from May 2021 to June 2022. This aimed to facilitate the early identification of situations where healthcare capacity may become overstretched.MethodsThe process involved a three-stage mixed methods approach. In the first stage, future deaths were predicted from the time series of reported cases and deaths to produce an initial alert level. In the second stage, this alert level was adjusted by incorporating a range of contextual indicators and accounting for the quality of information available using a Bayes classifier. In the third stage, countries with an alert level of ‘High’ or above were added to an operational watchlist and assistance was deployed as needed.ResultsSince June 2021, the system has supported the release of more than US$27 million from WHO emergency funding, over 450 000 rapid antigen diagnostic testing kits and over 6000 oxygen concentrators. Retrospective evaluation indicated that the first two stages were needed to maximise sensitivity, where 44% (IQR 29%–67%) of weekly watchlist alerts would not have been identified using only reported cases and deaths. The alerts were timely and valid in most cases; however, this could only be assessed on a non-representative sample of countries with hospitalisation data available.ConclusionsThe system provided a standardised approach to monitor the pandemic at the country level by incorporating all available data on epidemiological analytics and contextual assessments. While this system was developed for COVID-19, a similar system could be used for future outbreaks and emergencies, with necessary adjustments to parameters and indicators.

The COVID-19 pandemic has had a significant impact on how field-based research is being conducted globally. Given the challenges of undertaking fieldwork during epidemics and the need for mixed methods research to address the social, political, and economic issues related to epidemics, there is a small but growing body of evidence in this area. To contribute to the logistical and ethical considerations for conducting research during a pandemic, we draw on the challenges and lessons learnt from adapting methods for two research studies conducted in 2021 during the COVID-19 pandemic in low- and middle-income country (LMIC) settings: (1) in-person research in Uganda and (2) combined remote and in-person research in South and Southeast Asia. Our case studies focus on data collection and demonstrate the feasibility of conducting mixed methods research, even with many logistical and operational constraints. Social science research is often used to identify the context of specific issues, to provide a needs assessment, or inform longer-term planning; however, these case studies have shown the need to integrate social science research from the start of a health emergency and in a systematic way. Social science research during future health emergencies can also inform public health responses during the emergency. It is also crucial to collect social science data after health emergencies to inform future pandemic preparedness. Finally, researchers need to continue research on other public health issues that are ongoing even during a public health emergency.

Background Acute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology. Methods The number of monthly cases per province for AES, meningitis and diseases including dengue fever; influenza-like-illness (ILI); hand, foot, and mouth disease (HFMD); and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998–2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed. Results The national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection; temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included. Conclusions The positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination campaigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi .

Background Cross-border movements between districts bordering Uganda and the Democratic Republic of Congo (DRC) are common due to the interdependence between populations on either side, though this increases the risk of the international spread of infectious diseases. Due to the nature of their work, boda boda drivers (motorcycle taxis), taxis and truck drivers continue to cross the border during epidemics. However, perceived risk of contracting and spreading communicable diseases may be influenced by several factors such as the level of education, packaging and perception of health care messages, limited interaction with local socio-cultural dynamics or personal experiences. This study aims to explore differences in movement patterns and risk perceptions as factors for transmission among transport drivers in Ugandan border districts during the 2018–2020 Ebola Virus Disease (EVD) epidemic and the current COVID-19 pandemic. Methods Between May and June 2021, in-depth interviews and focus group discussions were conducted with transport drivers in three Ugandan districts bordering DRC (Kasese, Kisoro and Hoima). Participants were asked about their knowledge and beliefs about EVD and COVID-19, perceived risk during epidemics, reasons for, and travel patterns during the EVD epidemic and COVID- 19 pandemic. A thematic content analysis was applied. Results Participants’ awareness of EVD was higher than that of COVID-19 however, the risk of transmission of Ebola virus was perceived as a remote threat. Measures restricting mobility during the COVID-19 pandemic had a greater impact on transport drivers compared to those implemented during the EVD epidemic, and were perceived as prohibitive rather than protective, largely due to fear of reprisals by security officers. Despite this, drivers were unlikely to be able to comply with the restrictions as they relied on their work as a source of income. Conclusion The vulnerabilities of transport drivers should be considered in the context of epidemics such EVD and COVID-19 in Uganda. Policy makers should address these particularities and assess the impact of public health measures on transport drivers’ mobility and involve them in designing of mobility-relatedpolicies.

An estimated 73% of emerging infections are zoonotic in origin, with animal contact and encroachment on their habitats increasing the risk of spill-over events. In Vietnam, close exposure to a wide range of animals and animal products can lead to acquisition of zoonotic pathogens, a number of which cause central nervous system (CNS) infections. However, studies show the aetiology of CNS infections remains unknown in around half of cases. We used samples and data from hospitalised patients with CNS infections, enrolled into the Vietnam Initiative on Zoonotic Infections multicentre study, to determine the association between aetiology and animal contact including those in whom the cause was unknown. Among 933 patients, a pathogen or an antibody response to it was identified in 291 (31.2%, 95% CI 28.3-34.3%). The most common pathogens were Streptococcus suis (n = 91 (9.8%, 8.0-11.9%)) and Japanese encephalitis virus (JEV) (n = 72 (7.7%, 6.1-9.7%)). Commonly reported animal contact included keeping, raising or handling (n = 364 (39.0%, 35.9-42.2%)) and handling, cooking or consuming raw meat, blood or viscera in the 2 weeks prior to symptom onset (n = 371 (39.8%, 36.6-43.0%)), with the latter most commonly from pigs (n = 343 (36.9%, 33.8-40.1%). There was no association between an unknown aetiology and exposure to animals in a multivariate logistic regression. Further testing for unknown or undetected pathogens may increase diagnostic yield, however, given the high proportion of zoonotic pathogens and the presence of risk factors, increasing public awareness about zoonoses and preventive measures can be considered.

The coronavirus disease (COVID-19) presented a unique opportunity for the World Health Organization (WHO) to utilise public health intelligence (PHI) for pandemic response. WHO systematically captured mainly unstructured information (e.g. media articles, listservs, community-based reporting) for public health intelligence purposes. WHO used the Epidemic Intelligence from Open Sources (EIOS) system as one of the information sources for PHI. The processes and scope for PHI were adapted as the pandemic evolved and tailored to regional response needs. During the early months of the pandemic, media monitoring com-plemented official case and death reporting through the International Health Regulations mechanism and triggered alerts. As the pandemic evolved, PHI activi-ties prioritised identifying epidemiological trends to supplement the information available through indica-tor-based surveillance reported to WHO. The PHI scope evolved over time to include vaccine introduction, emergence of severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) variants, unusual clinical man-ifestations and upsurges in cases, hospitalisation and death incidences at subnational levels. Triaging the unprecedented high volume of information challenged surveillance activities but was managed by collabora-tive information sharing. The evolution of PHI activi-ties using multiple sources in WHO's response to the COVID-19 pandemic illustrates the future directions in which PHI methodologies could be developed and used.

Introduction Widespread armed conflict has affected Yemen since 2014. To date, the mortality toll of seven years of crisis, and any excess due to the COVID-19 pandemic, are not well quantified. We attempted to estimate population mortality during the pre-pandemic and pandemic periods in nine purposively selected urban and rural communities of southern and central Yemen (Aden and Ta’iz governorates), totalling > 100,000 people. Methods Within each study site, we collected lists of decedents between January 2014–March 2021 by interviewing different categories of key community informants, including community leaders, imams, healthcare workers, senior citizens and others. After linking records across lists based on key variables, we applied two-, three- or four-list capture-recapture analysis to estimate total death tolls. We also computed death rates by combining these estimates with population denominators, themselves subject to estimation. Results After interviewing 138 disproportionately (74.6%) male informants, we identified 2445 unique decedents. While informants recalled deaths throughout the study period, reported deaths among children were sparse: we thus restricted analysis to persons aged ≥ 15 years old. We noted a peak in reported deaths during May–July 2020, plausibly coinciding with the first COVID-19 wave. Death rate estimates featured uninformatively large confidence intervals, but appeared elevated compared to the non-crisis baseline, particularly in two sites where a large proportion of deaths were attributed to war injuries. There was no clear-cut evidence of excess mortality during the pandemic period. Conclusions We found some evidence of a peak in mortality during the early phase of the pandemic, but death rate estimates were otherwise too imprecise to enable strong inference on trends. Estimates suggested substantial mortality elevations from baseline during the crisis period, but are subject to serious potential biases. The study highlighted challenges of data collection in this insecure, politically contested environment.

Background Timely but accurate data collection is needed during health emergencies to inform public health responses. Often, an abundance of data is collected but not used. When outbreaks and other health events occur in remote and complex settings, operatives on the ground are often required to cover multiple tasks whilst working with limited resources. Tools that facilitate the collection of essential data during the early investigations of a potential public health event can support effective public health decision-making. We proposed to define the minimum set of quantitative information to collect whilst using electronic device or not. Here we present the process used to select the minimum information required to describe an outbreak of any cause during its initial stages and occurring in remote settings. Methods A working group of epidemiologists took part in two rounds of a Delphi process to categorise the variables to be included in an initial outbreak investigation form. This took place between January-June 2019 using an online survey. Results At a threshold of 75 %, consensus was reached for nineteen (23.2%) variables which were all classified as 'essential'. This increased to twenty-six (31.7%) variables when the threshold was reduced to 60% with all but one variable classified as 'essential'. Twenty-five of these variables were included in the 'Time zero initial case investigation' '(T0)' form which was shared with the members of the Rapid Response Team Knowledge Network for field testing and feedback. The form has been readily available online by WHO since September 2019. Conclusion This is the first known Delphi process used to determine the minimum variables needed for an outbreak investigation. The subsequent development of the T0 form should help to improve the efficiency and standardisation of data collection during emergencies and ultimately the quality of the data collected during field investigation.

Background: When the novel coronavirus – SARS-CoV-2 – started to spread globally, there was a call for social and behavioral scientists to conduct research to explore the wider socio-cultural contexts of coronavirus disease 2019 (COVID-19), to understand vulnerabilities, as well as to increase engagement within communities to facilitate adoption of public health measures. In this manuscript, we describe the protocol for a study conducted in Indonesia, Nepal, and Vietnam. In the study, we explore how the COVID-19 pandemic is affecting individuals and their communities. We focus on the wider health and economic impacts of COVID-19, in particular emerging and increased burden on mental health, as well as new or deepened vulnerabilities in the communities. The introduction of vaccines has added another layer of complexity and highlights differences in acceptance and inequalities around access. Methods: We use mixed methods, combining survey methods and social media surveillance to gain a picture of the general situation within each country, with in-depth qualitative methods to gain a deeper understanding of issues, coupled with a synergistic engagement component. We also include an exploration of the role of social media in revealing or driving perceptions of the pandemic more broadly. Participants include health workers and members of communities from 13 sites across the three countries. Data collection is spread across two phases. Phase 1 is concerned with exploring lived experiences, impacts on working lives and livelihoods, mental health and coping strategies. Phase 2 is concerned with acceptance of COVID-19 vaccines, factors that increase and reduce acceptance, and factors that influence access. Conclusions: We will disseminate findings in multiple ways including short reports and policy briefs, articles in peer-reviewed journals, and digital diaries will be edited into short films and uploaded onto social media sites.

Background: Approval for the use of COVID-19 vaccines has been granted in a number of countries but there are concerns that vaccine uptake may be low amongst certain groups. Methods: This study used a mixed methods approach based on online survey and an embedded quantitative/qualitative design to explore perceptions and attitudes that were associated with intention to either accept or refuse offers of vaccination in different demographic groups during the early stages of the UK's mass COVID-19 vaccination programme (December 2020). Analysis used multivariate logistic regression, structural text modeling and anthropological assessments. Results: Of 4,535 respondents, 85% (n = 3,859) were willing to have a COVID-19 vaccine. The rapidity of vaccine development and uncertainties about safety were common reasons for COVID-19 vaccine hesitancy. There was no evidence for the widespread influence of mis-information, although broader vaccine hesitancy was associated with intentions to refuse COVID-19 vaccines (OR 20.60, 95% CI 14.20–30.30, p < 0.001). Low levels of trust in the decision-making (OR 1.63, 95% CI 1.08, 2.48, p = 0.021) and truthfulness (OR 8.76, 95% CI 4.15–19.90, p < 0.001) of the UK government were independently associated with higher odds of refusing COVID-19 vaccines. Compared to political centrists, conservatives and liberals were, respectively, more (OR 2.05, 95%CI 1.51–2.80, p < 0.001) and less (OR 0.30, 95% CI 0.22–0.41, p < 0.001) likely to refuse offered vaccines. Those who were willing to be vaccinated cited both personal and public protection as reasons, with some alluding to having a sense of collective responsibility. Conclusion: Dominant narratives of COVID-19 vaccine hesitancy are misconceived as primarily being driven by misinformation. Key indicators of UK vaccine acceptance include prior behaviors, transparency of the scientific process of vaccine development, mistrust in science and leadership and individual political views. Vaccine programmes should leverage the sense of altruism, citizenship and collective responsibility that motivated many participants to get vaccinated.

Background The success of a government's COVID-19 control strategy relies on public trust and broad acceptance of response measures. We investigated public perceptions of the UK government's COVID-19 response, focusing on the relationship between trust and perceived transparency, during the first wave (April 2020) of the COVID-19 pandemic in the United Kingdom. Methods Anonymous survey data were collected (2020-04-06 to 2020-04-22) from 9,322 respondents, aged 20+ using an online questionnaire shared primarily through Facebook. We took an embedded-mixed-methods approach to data analysis. Missing data were imputed via multiple imputation. Binomial & multinomial logistic regression were used to detect associations between demographic characteristics and perceptions or opinions of the UK government's response to COVID-19. Structural topic modelling (STM), qualitative thematic coding of sub-sets of responses were then used to perform a thematic analysis of topics that were of interest to key demographic groups. Results Most respondents (95.1%) supported government enforcement of behaviour change. While 52.1% of respondents thought the government was making good decisions, differences were apparent across demographic groups, for example respondents from Scotland had lower odds of responding positively than respondents in London. Higher educational levels saw decreasing odds of having a positive opinion of the government response and decreasing household income associated with decreasing positive opinion. Of respondents who thought the government was not making good decisions 60% believed the economy was being prioritised over people and their health. Positive views on government decision-making were associated with positive views on government transparency about the COVID-19 response. Qualitative analysis about perceptions of government transparency highlighted five key themes: (1) the justification of opacity due to the condition of crisis, (2) generalised mistrust of politics, (3) concerns about the role of scientific evidence, (4) quality of government communication and (5) questions about political decision-making processes. Conclusion Our study suggests that trust is not homogenous across communities, and that generalised mistrust, concerns about the transparent use and communication of evidence and insights into decision-making processes can affect perceptions of the government's pandemic response. We recommend targeted community engagement, tailored to the experiences of different groups and a new focus on accountability and openness around how decisions are made in the response to the UK COVID-19 pandemic.

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018–2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection. Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo. Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations. Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

BackgroundODK provides software and standards that are popular solutions for off-grid electronic data collection and are the basis of related products like CommCare, Enketo, Ona, SurveyCTO and KoBoToolbox. In combination with the use of statistical analysis software such as R, these tools provide fully open-source options for off-grid use in public health data collection, management, analysis and reporting.ResultsNew functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring and near-real-time analysis during clinical research in health emergencies. We present open-source enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelisation of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo. During the 2018-2020 Ebola epidemic in the North Kivu & Ituri regions of Democratic Republic of Congo, ODK, Enketo and R were leveraged to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection. Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations.ConclusionsWe present open source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms (Ona, KoBoToolbox etc.) that are based on the ODK software and standards.FundingThis research is funded by the Department of Health and Social Care using UK Aid funding and is managed by the NIHR (PR-OD-1017-20001).

Objectives: We assessed whether lockdown had a disproportionate impact on physical activity behavior in groups who were, or who perceived themselves to be, at heightened risk from COVID-19. Methods: Physical activity intensity (none, mild, moderate, or vigorous) before and during the UK COVID-19 lockdown was self-reported by 9,190 adults between 2020-04-06 and 2020-04-22. Physician-diagnosed health conditions and topic composition of open-ended text on participants' coping strategies were tested for associations with changes in physical activity. Results: Most (63.9%) participants maintained their normal physical activity intensity during lockdown, 25.0% changed toward less intensive activity and 11.1% were doing more. Doing less intensive physical activity was associated with obesity (OR 1.25, 95% CI 1.08-1.42), hypertension (OR 1.25, 1.10-1.40), lung disease (OR 1.23, 1.08-1.38), depression (OR 2.05, 1.89-2.21), and disability (OR 2.13, 1.87-2.39). Being female (OR 1.25, 1.12-1.38), living alone (OR 1.20, 1.05-1.34), or without access to a garden (OR 1.74, 1.56-1.91) were also associated with doing less intensive physical activity, but being in the highest income group (OR 1.73, 1.37-2.09) or having school-age children (OR 1.29, 1.10-1.49) were associated with doing more. Younger adults were more likely to change their PA behavior compared to older adults. Structural topic modeling of narratives on coping strategies revealed associations between changes in physical activity and perceptions of personal or familial risks at work or at home. Conclusions: Policies on maintaining or improving physical activity intensity during lockdowns should consider (1) vulnerable groups of adults including those with chronic diseases or self-perceptions of being at risk and (2) the importance of access to green or open spaces in which to exercise.