Dataset Information

Containing pandemics through targeted testing of households.

ABSTRACT:

Background

While invasive social distancing measures have proven efficient to control the spread of pandemics failing wide-scale deployment of vaccines, they carry vast societal costs. The development of a diagnostic methodology for identifying COVID-19 infection through simple testing was a reality only a few weeks after the novel virus was officially announced. Thus, we were interested in exploring the ability of regular testing of non-symptomatic people to reduce cases and thereby offer a non-pharmaceutical tool for controlling the spread of a pandemic.

Methods

We developed a data-driven individual-based epidemiological network model in order to investigate epidemic countermeasures. This models is based on high-resolution demographic data for each municipality in Norway, and each person in the model is subject to Susceptible-Exposed-Infectious-Recovered (SEIR) dynamics. The model was calibrated against hospitalization data in Oslo, Norway, a city with a population of 700k which we have used as the simulations focus.

Results

Finding that large households function as hubs for the propagation of COVID-19, we assess the intervention efficiency of targeted pooled household testing (TPHT) repeatedly. For an outbreak with reproductive number R=1.4, we find that weekly TPHT of the 25% largest households brings R below unity. For the case of R=1.2, our results suggest that TPHT with the largest 25% of households every three days in an urban area is as effective as a lockdown in curbing the outbreak. Our investigations of different disease parameters suggest that these results are markedly improved for disease variants that more easily infect young people, and when compliance with self-isolation rules is less than perfect among suspected symptomatic cases. These results are quite robust to changes in the testing frequency, city size, and the household-size distribution. Our results are robust even with only 50% of households willing to participate in TPHT, provided the total number of tests stay unchanged.

Conclusions

Pooled and targeted household testing appears to be a powerful non-pharmaceutical alternative to more invasive social-distancing and lock-down measures as a localized early response to contain epidemic outbreaks.

SUBMITTER: Voigt A

PROVIDER: S-EPMC8189703 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The widespread use of antigen-detection rapid diagnostic tests (Ag-RDTs) has revolutionized SARS-CoV-2 (COVID-19) testing, particularly through the option of self-testing. The full extent of Ag-RDT utilization for self-testing, however, remains largely unexplored. To inform the development of WHO guidance on COVID-19 self-testing, we conducted a global consultation to gather the views and experiences of policy makers, researchers, and implementers worldwide. The consultation was conducted by disseminating a WHO questionnaire through professional networks via email and social media, encouraging onward sharing. We used a cross-sectional design with both closed and open-ended questions related to policy and program information concerning the regulation, availability, target population, indications, implementation, benefits, and challenges of COVID-19 self-testing (C19ST). We defined self-testing as tests performed and interpreted by an untrained individual, often at home. Descriptive summaries, cross-tabulations, and proportions were used to calculate outcomes at the global level and by WHO region and World Bank income classifications. All information was collated and reported according to WHO guideline development standards and practice for global consultations. Between 01 and 11 February 2022, 844 individuals from 139 countries responded to the survey, with 45% reporting affiliation with governments and 47% operating at the national level. 504 respondents from 101 countries reported policies supporting C19ST for a range of use cases, including symptomatic and asymptomatic populations. More respondents from low-and-middle-income countries (LMICs) than high-income countries (HICs) reported a lack of an C19ST policy (61 vs 11 countries) and low population-level reach of C19ST. Respondents with C19ST experience perceived that the tests were mostly acceptable to target populations, provided significant benefits, and highlighted several key challenges to be addressed for increased success. Reported costs varied widely, ranging from specific programmes enabling free access to certain users and others with high costs via the private sector. Based on this consultation, systems for the regulatory review, policy development and implementation of C19ST appeared to be much more common in HIC when compared to LIC in early 2022, though most respondents indicated self-testing was available to some extent (101 out of 139 countries) in their country. Addressing such global inequities is critical for ensuring access to innovative and impactful interventions in the context of a public health emergency of international concern. The challenges and opportunities highlighted by key stakeholders could be valuable to consider as future testing strategies are being set for outbreak-prone diseases.

Project description:The data was collected in the Karagwe and Kyerwa districts of the Kagera region in north-west Tanzania. It encompasses 150 smallholder farming households, which were interviewed on the composition of their household, agricultural production and use of organic farm waste. The data covers the two previous rainy seasons and the associated vegetation periods between September 2016 and August 2017. The knowledge of experts from the following institutions was included in the discussion on the selection criteria: two local non-profit organisations, i.e., WOMEDA and the MAVUNO Project; the International Institute of Tropical Agriculture (IITA); and the National Land Use Planning Commission (NLUPC). Households were selected for inclusion if all of the following applied to them: 1) less than 10 acres of land (4.7 ha) registered in the village offices, 2) no agricultural training, and 3) decline in the fertility of their land since they started farming (self-reported). We selected 150 smallholder households out of a pool of 5,000 households known to WOMEDA in six divisions of the Kyerwa and Karagwe districts. The questionnaire contained 54 questions. The original language of the survey was Kiswahili. All interviews were audio recorded. The answers were digitalised and translated into English. The data set contains the raw data with 130 quantitative and qualitative variables. For quantitative variables, the only analysis that was made was the conversion of units, e.g., land area was converted from acres to hectares, harvest from buckets to kilograms and then to tons, and heads of livestock to Tropical Livestock Units (TLU). Qualitative variables were summarised into categories. All data has been anonymised. The data set includes geographical variables, household information, agricultural information, gender-specific responsibilities, economic data, farm waste management, and water, energy and food availability (Water-Energy-Food (WEF) Nexus). Variables are written in italics. The following geographical variables are part of the data set: district, division, ward, village, hamlet, longitude, latitude, and altitude. Household information includes start of farming, household size, gender and age of household members. Agricultural information includes land size, size of homegarden, crops, livestock and livestock keeping, trees, and access to forest. Gender-specific responsibilities includes producing and exchanging seeds, weed control, terracing, distributing organic material to the fields, care of annual and perennial crops, harvesting of crops, decisions about the harvest and animal products, selling and buying products, working on their own farm and off-farm, cooking, storing food, collecting and caring for drinking water, washing, and toilet cleaning. Economic data includes distance to the market, journey time to market, transport methods, labourers employed by the household, working off-farm, and assets such as type of house. Variables relevant to the WEF Nexus are drinking water source and treatment, meals per day, months without food, cooking fuel, and type of toilet. Variables on farm waste management are the use of crop residues, food and kitchen waste, livestock manure, cooking ash, animal bones, and human urine and faeces. The data can be potentially reused and further developed for the purpose of agricultural production analysis, socio-economic analysis, comparison to other regions, conceptualisation of waste and nutrient management, establishment of land use concepts, and further analysis on food security and healthy diets.