EpiJSON: A unified data-format for epidemiology

AbstractEpidemiology relies on data but the divergent ways data are recorded and transferred, both within and between outbreaks, and the expanding range of data-types are creating an increasingly complex problem for the discipline. There is a need for a consistent, interpretable and precise way to transfer data while maintaining its fidelity. We introduce ‘EpiJSON’, a new, flexible, and standards-compliant format for the interchange of epidemiological data using JavaScript Object Notation. This format is designed to enable the widest range of epidemiological data to be unambiguously held and transferred between people, software and institutions. In this paper, we provide a full description of the format and a discussion of the design decisions made. We introduce a schema enabling automatic checks of the validity of data stored as EpiJSON, which can serve as a basis for the development of additional tools. In addition, we also present the R package ‘repijson’ which provides conversion tools between this format, line-list data and pre-existing analysis tools. An example is given to illustrate how EpiJSON can be used to store line list data. EpiJSON, designed around modern standards for interchange of information on the internet, is simple to implement, read and check. As such, it provides an ideal new standard for epidemiological, and other, data transfer to the fast-growing open-source platform for the analysis of disease outbreaks

Malaria Data by District: An open-source web application for increasing access to malaria information

In recent years, the mapping of diseases has improved considerably in extent, resolution and accuracy (Kraemer et al., 2016). Increasingly, data and related spatial outputs are being made publicly available (Briand et al., 2018; Flueckiger et al., 2015). However, the full potential of associated modelled outputs will only be realised if data are accessed and used to inform local decision making. Recent reviews have suggested that data repositories are mainly targeted toward researchers rather than decision makers and that there is a need to improve indicator data use in low- and middle-income countries (Briand et al., 2018; Omumbo et al., 2013). We describe the development of an open-source web application, MaDD (Malaria Data by District) (Tomlinson et al., 2019), that enables disease distribution data to be more accessible at a local level. The Malaria Atlas Project (MAP) is an international consortium which provides geographical information on diverse aspects of malaria epidemiology (Hay & Snow, 2006). The open-access data generated by MAP have the potential to influence policy at the national and subnational level (Hay & Snow, 2006; Moyes et al., 2013). The project includes sophisticated interpolation models that allow inference of malaria prevalence, as detailed in national and regional indicator surveys, at non-sampled locations (Giorgi et al., 2018; Hay & Snow, 2006). Getting contemporary estimates of malaria metrics to policy makers is essential, but barriers to acceptance exist, notably for modelled predictions; these include the complexity of the statistics described within output reports, and the description of assumptions made during the modelling process (Whitty, 2015). Additional barriers include the sheer wealth of data available, making it difficult to find and choose data surfaces despite central repositories that may be easily navigable. These factors have contributed towards a general lack of modelled outputs being used by local-level implementation programmes in Africa (Omumbo et al., 2013). Most modelled MAP data are provided as spatial estimates, presented as 5 × 5 km gridded surfaces, for example, estimates of Plasmodium falciparum prevalence and mortality, estimates of indoor residual spraying coverage and estimates of dominant vector species distributions and abundance (Bhatt et al., 2015; Gething et al., 2016; Sinka et al., 2016). Though data generated at this spatial resolution provides a visual indication of subnational disparities, it is not immediately clear how these data may be used directly in operational decision-making. For modelled data to be utilised by operational staff at a local level, there is a requirement for additional tools and the ability to convert such data into operationally useful metrics at the level of administrative units (Knight et al., 2016; Omumbo et al., 2013; Whitty, 2015). Data curated by MAP can already be accessed via online interactive maps (Malaria Atlas Project, 2019), an online country profiles tool and the malariaAtlas R package (Pfeffer et al., 2018). These are powerful tools enabling access to MAP generated data that do include data summaries by administrative units. However, because of the wealth of data and functionality it is not straightforward to find and use these tools to perform district-level comparisons. Here, we present an application that allows rapid generation and comparison of summary statistics for a select suite of malaria indicator variables at the sub-national administrative level. MaDD is open-source and coded in R, so it can easily be modified to address local needs (R Core Team, 2019). This is a step towards developing tools for local decision makers to inform questions such as, “where should we prioritise the targeting of IRS rounds this season?”

Measuring, manipulating and exploiting behaviours of adult mosquitoes to optimise malaria vector control impact.

Residual malaria transmission can persist despite high coverage with effective long-lasting insecticidal nets (LLINs) and/or indoor residual spraying (IRS), because many vector mosquitoes evade them by feeding on animals, feeding outdoors, resting outdoors or rapidly exiting from houses after entering them. However, many of these behaviours that render vectors resilient to control with IRS and LLINs also make them vulnerable to some emerging new alternative interventions. Furthermore, vector control measures targeting preferred behaviours of mosquitoes often force them to express previously rare alternative behaviours, which can then be targeted with these complementary new interventions. For example, deployment of LLINs against vectors that historically fed predominantly indoors on humans typically results in persisting transmission by residual populations that survive by feeding outdoors on humans and animals, where they may then be targeted with vapour-phase insecticides and veterinary insecticides, respectively. So while the ability of mosquitoes to express alternative behaviours limits the impact of LLINs and IRS, it also creates measurable and unprecedented opportunities for deploying complementary additional approaches that would otherwise be ineffective. Now that more diverse vector control methods are finally becoming available, well-established entomological field techniques for surveying adult mosquito behaviours should be fully exploited by national malaria control programmes, to rationally and adaptively map out new opportunities for their effective deployment

A rapid and reproducible picture of open access health facility data in Africa to support the COVID-19 response

Background: Open data on the locations and services provided by health facilities in some countries have allowed the development of software tools contributing to COVID-19 response. The UN and WHO encourage countries to make health facility location data open, to encourage use and improvement. We provide a summary of open access health facility location data in Africa using re-useable code. We aim to support data analysts developing software tools to address COVID-19 response in individual countries. In Africa there are currently three main sources of such data; 1) direct from national ministries of health, 2) a database for sub-Saharan Africa collated and published by a team from KEMRI-Wellcome Trust Research Programme and now hosted by WHO, and 3) The Global Healthsites Mapping Project in collaboration with OpenStreetMap. Methods: We searched for and documented official national facility location data that were openly available. We developed re-useable open-source R code to summarise and visualise facility location data by country from the three sources. This re-useable code is used to provide a web user interface allowing data exploration through maps and plots of facility type. Results: Out of 53 African countries, seven provide an official open facility list that can be downloaded and analysed reproducibly. Considering all three sources, there are over 185,000 health facility locations available for Africa. However, there are differences and overlaps between sources and a lack of data on capacities and service provision. Conclusions: We suggest that these summaries and tools will encourage greater use of existing health facility location data, incentivise further improvements in the provision of those data by national suppliers, and encourage collaboration within wider data communities. The tools are a part of the afrimapr project, actively developing R building blocks to facilitate the use of health data in Africa

Visitor expenditure estimation for grocery store location planning: a case study of Cornwall

Visitor expenditure is an important driver of demand in many local economies, supporting a range of services and facilities which may not be viable based solely on residential demand. In areas where self-catering accommodation is prevalent visitor demand makes up a considerable proportion of sales and revenue within grocery stores, yet this form of visitor consumption is commonly overlooked in supply and demand-side estimates of visitor spend. As such, store location planning in tourist resorts, decisions about local service provision and the local economic impacts of tourism are based on very limited demand-side estimates of visitor spend. Using Cornwall, South West England as a study area, we outline a methodology and data sources to estimate small-area visitor grocery spend. We use self-catering accommodation provision, utilisation and visitor expenditure rates as key factors driving visitor spend. We identify that the use of visitor accommodation accounts for the spatial and temporal complexities of visitor demand that may be overlooked when using alternative approaches, such as the up-scaling of residential demand. Using a spatial interaction model, we demonstrate that our expenditure estimates can be used to generate store level revenue estimation within tourist resorts, and we make a number of recommendations for service provision and store location planning in these areas

ResistanceSim: development and acceptability study of a serious game to improve understanding of insecticide resistance management in vector control programmes.

The use of insecticides is the cornerstone of effective malaria vector control. However, the last two decades has seen the ubiquitous use of insecticides, predominantly pyrethroids, causing widespread insecticide resistance and compromising the effectiveness of vector control. Considerable efforts to develop new active ingredients and interventions are underway. However, it is essential to deploy strategies to mitigate the impact of insecticide resistance now, both to maintain the efficacy of currently available tools as well as to ensure the sustainability of new tools as they come to market. Although the World Health Organization disseminated best practice guidelines for insecticide resistance management (IRM), Rollback Malaria's Vector Control Working Group identified the lack of practical knowledge of IRM as the primary gap in the translation of evidence into policy. ResistanceSim is a capacity strengthening tool designed to address this gap. The development process involved frequent stakeholder consultation, including two separate workshops. These workshops defined the learning objectives, target audience, and the role of mathematical models in the game. Software development phases were interspersed with frequent user testing, resulting in an iterative design process. User feedback was evaluated via questionnaires with Likert-scale and open-ended questions. The game was regularly evaluated by subject-area experts through meetings of an external advisory panel. Through these processes, a series of learning domains were identified and a set of specific learning objectives for each domain were defined to be communicated to vector control programme personnel. A simple "game model" was proposed that produces realistic outputs based on player strategy and also runs in real-time. Early testing sessions revealed numerous usability issues that prevented adequate player engagement. After extensive revisions, later testing sessions indicated that the tool would be a valuable addition to IRM training