Distinct Red Blotch Disease Epidemiological Dynamics in Two Nearby Vineyards.

Grapevine red blotch virus (GRBV) causes red blotch disease and is transmitted by the three-cornered alfalfa hopper, Spissistilus festinus. GRBV isolates belong to a minor phylogenetic clade 1 and a predominant clade 2. Spatiotemporal disease dynamics were monitored in a 1-hectare 'Merlot' vineyard planted in California in 2015. Annual surveys first revealed disease onset in 2018 and a 1.6% disease incidence in 2022. Ordinary runs and phylogenetic analyses documented significant aggregation of vines infected with GRBV clade 1 isolates in one corner of the vineyard (Z = -4.99), despite being surrounded by clade 2 isolates. This aggregation of vines harboring isolates from a non-prevalent clade is likely due to infected rootstock material at planting. GRBV clade 1 isolates were predominant in 2018-2019 but displaced by clade 2 isolates in 2021-2022, suggesting an influx of the latter isolates from outside sources. This study is the first report of red blotch disease progress immediately after vineyard establishment. A nearby 1.5-hectare 'Cabernet Sauvignon' vineyard planted in 2008 with clone 4 (CS4) and 169 (CS169) vines was also surveyed. Most CS4 vines that exhibited disease symptoms one-year post-planting, likely due to infected scion material, were aggregated (Z = -1.73). GRBV isolates of both clades were found in the CS4 vines. Disease incidence was only 1.4% in non-infected CS169 vines in 2022 with sporadic infections of isolates from both clades occurring via secondary spread. Through disentangling GRBV infections due to the planting material and S. festinus-mediated transmission, this study illustrated how the primary virus source influences epidemiological dynamics of red blotch disease.

Gaps seen in China's crackdown on wildlife trade.

Stricter rules could prevent disease outbreaks, but allowances for fur farming spur concern.

Detection of Influenza D-Specific Antibodies in Bulk Tank Milk from Swedish Dairy Farms.

Influenza D virus (IDV) has been detected in bovine respiratory disease (BRD) outbreaks, and experimental studies demonstrated this virus's capacity to cause lesions in the respiratory tract. In addition, IDV-specific antibodies were detected in human sera, which indicated that this virus plays a potential zoonotic role. The present study aimed to extend our knowledge about the epidemiologic situation of IDV in Swedish dairy farms, using bulk tank milk (BTM) samples for the detection of IDV antibodies. A total of 461 and 338 BTM samples collected during 2019 and 2020, respectively, were analyzed with an in-house indirect ELISA. In total, 147 (32%) and 135 (40%) samples were IDV-antibody-positive in 2019 and 2020, respectively. Overall, 2/125 (2%), 11/157 (7%) and 269/517 (52%) of the samples were IDV-antibody-positive in the northern, middle and southern regions of Sweden. The highest proportion of positive samples was repeatedly detected in the south, in the county of Halland, which is one of the counties with the highest cattle density in the country. In order to understand the epidemiology of IDV, further research in different cattle populations and in humans is required.

Cryptic SARS-CoV-2 lineage identified on two mink farms as a possible result of long-term undetected circulation in an unknown animal reservoir, Poland, November 2022 to January 2023.

In late 2022 and early 2023, SARS-CoV-2 infections were detected on three mink farms in Poland situated within a few km from each other. Whole-genome sequencing of the viruses on two of the farms showed that they were related to a virus identified in humans in the same region 2 years before (B.1.1.307 lineage). Many mutations were found, including in the S protein typical of adaptations to the mink host. The origin of the virus remains to be determined.

Early Identification of Crop Type for Smallholder Farming Systems Using Deep Learning on Time-Series Sentinel-2 Imagery.

Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food security. Reliable crop type maps can play an essential role in monitoring crops, estimating yields, and maintaining smooth food supplies. However, these maps are not available for developing countries until crops have matured and are about to be harvested. The use of remote sensing for accurate crop-type mapping in the first few weeks of sowing remains challenging. Smallholder farming systems and diverse crop types further complicate the challenge. For this study, a ground-based survey is carried out to map fields by recording the coordinates and planted crops in respective fields. The time-series images of the mapped fields are acquired from the Sentinel-2 satellite. A deep learning-based long short-term memory network is used for the accurate mapping of crops at an early growth stage. Results show that staple crops, including rice, wheat, and sugarcane, are classified with 93.77% accuracy as early as the first four weeks of sowing. The proposed method can be applied on a large scale to effectively map crop types for smallholder farms at an early stage, allowing the authorities to plan a seamless availability of food.

Proximity to livestock farms and COVID-19 in the Netherlands, 2020-2021.

OBJECTIVES: In the Netherlands, during the first phase of the COVID-19 epidemic, the hotspot of COVID-19 overlapped with the country's main livestock area, while in subsequent phases this distinct spatial pattern disappeared. Previous studies show that living near livestock farms influence human respiratory health and immunological responses. This study aimed to explore whether proximity to livestock was associated with SARS-CoV-2 infection. METHODS: The study population was the population of the Netherlands excluding the very strongly urbanised areas and border areas, on January 1, 2019 (12, 628, 244 individuals). The cases are the individuals reported with a laboratory-confirmed positive SARS-CoV-2 test with onset before January 1, 2022 (2, 223, 692 individuals). For each individual, we calculated distance to nearest livestock farm (cattle, goat, sheep, pig, poultry, horse, rabbit, mink). The associations between residential (6-digit postal-code) distance to the nearest livestock farm and individuals' SARS-CoV-2 status was studied with multilevel logistic regression models. Models were adjusted for individuals' age categories, the social status of the postal code area, particulate matter (PM10)- and nitrogen dioxide (NO2)-concentrations. We analysed data for the entire period and population as well as separately for eight time periods (Jan-Mar, Apr-Jun, Jul-Sep and Oct-Dec in 2020 and 2021), four geographic areas of the Netherlands (north, east, west and south), and for five age categories (0-14, 15-24, 25-44, 45-64 and > 65 years). RESULTS: Over the period 2020-2021, individuals' SARS-CoV-2 status was associated with living closer to livestock farms. This association increased from an Odds Ratio (OR) of 1.01 (95% Confidence Interval [CI] 1.01-1.02) for patients living at a distance of 751-1000 m to a farm to an OR of 1.04 (95% CI 1.04-1.04), 1.07 (95% CI 1.06-1.07) and 1.11 (95% CI 1.10-1.12) for patients living in the more proximate 501-750 m, 251-500m and 0-250 m zones around farms, all relative to patients living further than 1000 m around farms. This association was observed in three out of four quarters of the year in both 2020 and 2021, and in all studied geographic areas and age groups. CONCLUSIONS: In this exploratory study with individual SARS-CoV-2 notification data and high-resolution spatial data associations were found between living near livestock farms and individuals' SARS-CoV-2 status in the Netherlands. Verification of the results in other countries is warranted, as well as investigations into possible underlying exposures and mechanisms.

Modeling between-farm transmission dynamics of porcine epidemic diarrhea virus: Characterizing the dominant transmission routes.

The role of transportation vehicles, pig movement between farms, proximity to infected premises, and feed deliveries has not been fully considered in the dissemination dynamics of porcine epidemic diarrhea virus (PEDV). This has limited efforts for disease prevention, control and elimination restricting the development of risk-based resource allocation to the most relevant modes of PEDV dissemination. Here, we modeled nine pathways of between-farm transmission represented by a contact network of pig movements between sites, farm-to-farm proximity (local transmission), four distinct contact networks of transportation vehicles (trucks that transport pigs from farm-to-farm and farm-to-markets, as well as trucks transporting feed and staff), the volume of animal by-products in feed diets (e.g., fat and meat-and-bone-meal) to reproduce PEDV transmission dynamics. The model was calibrated in space and time with weekly PEDV outbreaks. We investigated the model performance to identify outbreak locations and the contribution of each route in the dissemination of PEDV. The model estimated that 42.7% of the infections in sow farms were related to vehicles transporting feed, 34.5% of infected nurseries were associated with vehicles transporting pigs between farms, and for both farm types, local transmission or pig movements were the next most relevant transmission routes. On the other hand, finishers were most often (31.4%) infected via local transmission, followed by the vehicles transporting feed and pigs between farms. Feed ingredients did not significantly improve model calibration metrics, sensitivity, and specificity; therefore, it was considered to have a negligible contribution in the dissemination of PEDV. The proposed modeling framework provides an evaluation of PEDV transmission dynamics, ranking the most important routes of PEDV dissemination and granting the swine industry valuable information to focus efforts and resources on the most important transmission routes.

Influx of Backyard Farming with Limited Biosecurity Due to the COVID-19 Pandemic Carries an Increased Risk of Zoonotic Spillover in Cambodia.

Backyard farming with limited biosecurity creates a massive potential for zoonotic spillover. Cambodia, a developing nation in Southeast Asia, is a hub for emerging and endemic infectious diseases. Due to pandemic-induced job losses in the tourism sector, rumors suggest that many former Cambodian tour guides have turned to backyard farming as a source of income and food security. A cross-sectional study including 331 tour guides and 69 poultry farmers in Cambodia before and during the novel coronavirus disease 2019 (COVID-19) pandemic was conducted. Participants were administered a survey to assess food security, income, and general farming practices. Survey data were collected to evaluate the risk perceptions for avian influenza virus (AIV), antimicrobial resistance (AMR), and general biosecurity management implemented on these poultry farms. Overall, food security decreased for 80.1% of the tour guides during the COVID-19 pandemic. Approximately 21% of the tour guides interviewed used backyard poultry farming to supplement losses of income and food insecurity during the COVID-19 pandemic, with a significantly higher risk than for traditional poultry farmers. Agricultural intensification in Cambodia due to the COVID-19 pandemic has caused an influx of makeshift farms with limited biosecurity. Inadequate biosecurity measures in animal farms can facilitate spillover and contribute to future pandemics. Improved biosecurity and robust viral surveillance systems are critical for reducing the risk of spillover from backyard farms. IMPORTANCE While this study highlights COVID-19-associated changes in poultry production at a small scale in Cambodia, poultry production is expected to expand due to an increase in the global demand for poultry protein during the pandemic, changes in urbanization, and the reduction of the global pork supply caused by African swine fever (ASF). The global demand and surge in poultry products, combined with inadequate biosecurity methods, can lead to an increased risk of domestic animal and human spillovers of zoonotic pathogens such as avian influenza. Countries in regions of endemicity are often plagued by complex emergency situations (i.e., food insecurity and economic fallouts) that hinder efforts to effectively address the emergence (or reemergence) of zoonotic diseases. Thus, novel surveillance strategies for endemic and emerging infectious diseases require robust surveillance systems and biosecurity training programs to prevent future global pandemics.

One Health Investigation of SARS-CoV-2 in People and Animals on Multiple Mink Farms in Utah.

From July−November 2020, mink (Neogale vison) on 12 Utah farms experienced an increase in mortality rates due to confirmed SARS-CoV-2 infection. We conducted epidemiologic investigations on six farms to identify the source of virus introduction, track cross-species transmission, and assess viral evolution. Interviews were conducted and specimens were collected from persons living or working on participating farms and from multiple animal species. Swabs and sera were tested by SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) and serological assays, respectively. Whole genome sequencing was attempted for specimens with cycle threshold values <30. Evidence of SARS-CoV-2 infection was detected by rRT-PCR or serology in ≥1 person, farmed mink, dog, and/or feral cat on each farm. Sequence analysis showed high similarity between mink and human sequences on corresponding farms. On farms sampled at multiple time points, mink tested rRT-PCR positive up to 16 weeks post-onset of increased mortality. Workers likely introduced SARS-CoV-2 to mink, and mink transmitted SARS-CoV-2 to other animal species; mink-to-human transmission was not identified. Our findings provide critical evidence to support interventions to prevent and manage SARS-CoV-2 in people and animals on mink farms and emphasizes the importance of a One Health approach to address emerging zoonoses.

Flies (Insecta, Diptera) collected in the environment of dairy farms as carriers of Rotavirus A and betacoronavirus.

AIMS: We aimed to investigate the prevalence of rotavirus and coronavirus in dipterans that commonly inhabit the environment of dairy farms. METHODS AND RESULTS: We collected 217 insect specimens from nine dairy farms, which were examined through hemi-nested RT-PCR followed by Sanger sequencing in search of VP1 and N genes for rotavirus and bovine coronavirus-BCoV, respectively. With a predominance of Muscidae (152/217 = 70%) 11 families of Diptera were identified. Rotavirus A (RVA) and betacoronavirus (BCoV) were detected in 14.7% (32/217) and 4.6% (10/217) of the dipterans, respectively. Sequencing of the amplicons was possible for 11.5% (25/217) of RVA and 0.5% (1/217) of BCoV, confirming the presence of these pathogens. CONCLUSIONS: Our findings highlight the role of dipterans as carriers of RVA and BCoV of great relevance for public and animal health.

Improving wasting among children under-5 years in Malawi: The role of farm input subsidies.

Wasting among children under-5 years remains a public health problem in Malawi, despite the quest to improve food availability through Farm Input Subsidy Program (FISP). As such, the study examined the link between FISP and child wasting. Using Malawi Integrated Household Panel Surveys for 2013, 2016, and 2019, two-stage least squares approach was employed to run a Cobb Douglas production function and a correlated Random Effects (CRE) Model to account for endogeneity challenges and an unbalanced panel dataset. The study hypothesized the role of FISP to dietary diversity at the household level on child wasting [weight-for-height (WHZ)]. Based on the analysis, the study found that household access to FISP coupons was not a stand-alone predictor for low wasting among children under-5 years. However, increased maize production due to FISP coupon access significantly correlated with lower wasting likelihood incidences at the household level. Worth to note, that in 2015/16, households that had accessed FISP coupons and were in the central region had higher wasting probabilities among the children under-5 years in Malawi compared to other counterparts panels. This implies challenges to addressing wasting among children under-5 years- which can be attributed to higher redemption costs of the FISP coupon. Therefore, the current study suggests that input subsidies can improve the reduction of wasting among children under-5 years through specific pathways, among them, increased maize production and considering appropriate targeted approaches to ensure households access the inputs for sustained food availability, which in turn enhances improved the children under-5 years health dividends in Malawi.

The impact of crop specialization on nutritional intake: Evidence from farm households in China.

BACKGROUND: In the wake of the severe impact of COVID-19 on the food security of the vulnerable groups in rural areas, the issue of how to achieve the Sustainable Development Goals 2 aims to "Zero Hunger" (SDG 2) and ensure the food safety of farmers has drawn unprecedented attention. Nutritional intake is generally used as an important indicator to reflect family food security. Under the background that Chinese farmers have gradually changed from the traditional diversified production mode to the specialized production of crops, the main purpose of this article is to explore what are the impact of crop specialization on farmers' nutritional intake? Could the specialization of crop production be taken as an important measure to ensure the food safety of farmers and achieve the SDG 2? METHODS: Based on the micro-survey data from 866 farmer households in China, this paper using Seemingly Unrelated Regressions model, Group Regression model and Mediating Effect model to analyze the average and heterogeneous effects of crop specialization on the nutritional intake of farmers, as well as the mediating effect of income. In addition, robustness test and endogenous treatment were performed by using alternative explanatory variables and IV-2SLS method was used to estimate the results. RESULTS: After correcting for endogenous bias, crop specialization had a significant negative impact on energy intake and fat intake of farmers at the statistical level of 5% and 1% respectively, especially for farmers in mountainous areas. Household income played a mediating effect on the effect of crop specialization on farmers' energy and fat intake, and the proportion of the masking effect was 8.43% and 8.96% respectively. In addition, household financial capital and social capital have a significant positive impact on farmers' nutritional intake. CONCLUSIONS: Crop specialization cannot guarantee the food safety of farmers in terms of nutritional intake. However, when the development trend of crop specialization is irreversible, more attention should be paid to improving the level of various livelihood capital of farmers, especially those in mountainous areas, and to continuously increasing their income to ease and ultimately eliminate the negative impact of crop specialization on farmers' nutritional intake, which finally make everyone realize the SDG 2.

GPS Tracking of Free-Roaming Cats (Felis catus) on SARS-CoV-2-Infected Mink Farms in Utah.

Zoonotic transmission of SARS-CoV-2 from infected humans to other animals has been documented around the world, most notably in mink farming operations in Europe and the United States. Outbreaks of SARS-CoV-2 on Utah mink farms began in late July 2020 and resulted in high mink mortality. An investigation of these outbreaks revealed active and past SARS-CoV-2 infections in free-roaming and in feral cats living on or near several mink farms. Cats were captured using live traps, were sampled, fitted with GPS collars, and released on the farms. GPS tracking of these cats show they made frequent visits to mink sheds, moved freely around the affected farms, and visited surrounding residential properties and neighborhoods on multiple occasions, making them potential low risk vectors of additional SARS-CoV-2 spread in local communities.

Molecular survey of infectious bronchitis virus on poultry farms in Gifu Prefecture, Japan from 2021 to 2022 by RT-PCR with an enhanced level of detection sensitivity for the S1 gene.

Infectious bronchitis virus (IBV) is the causative agent of infectious bronchitis (IB) in chickens. There is a correlation between cross-protection and percentage of similarity between nucleotide sequences encoding the S1 subunit, which is responsible for generating neutralizing and serotype-specific antibodies. Therefore, RT-PCR is commonly used to amplify the IBV-S1 gene following DNA sequencing in order to predict the efficacy of vaccines against IBV strains. We successfully enhanced the sensitivity for detection of the IBV-S1 gene by second PCR after purification of the 1st RT-PCR product. Using that method, we obtained detailed information on the prevalence of IBV on poultry farms in Gifu Prefecture, Japan. The IBV-S1 gene detection method used in the current study will enable accurate information on the prevalence of IBV in Japan to be obtained.

A Cloud Enabled Crop Recommendation Platform for Machine Learning-Driven Precision Farming.

Modern agriculture incorporated a portfolio of technologies to meet the current demand for agricultural food production, in terms of both quality and quantity. In this technology-driven farming era, this portfolio of technologies has aided farmers to overcome many of the challenges associated with their farming activities by enabling precise and timely decision making on the basis of data that are observed and subsequently converged. In this regard, Artificial Intelligence (AI) holds a key place, whereby it can assist key stakeholders in making precise decisions regarding the conditions on their farms. Machine Learning (ML), which is a branch of AI, enables systems to learn and improve from their experience without explicitly being programmed, by imitating intelligent behavior in solving tasks in a manner that requires low computational power. For the time being, ML is involved in a variety of aspects of farming, assisting ranchers in making smarter decisions on the basis of the observed data. In this study, we provide an overview of AI-driven precision farming/agriculture with related work and then propose a novel cloud-based ML-powered crop recommendation platform to assist farmers in deciding which crops need to be harvested based on a variety of known parameters. Moreover, in this paper, we compare five predictive ML algorithms-K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Support Vector Machine (SVM)-to identify the best-performing ML algorithm on which to build our recommendation platform as a cloud-based service with the intention of offering precision farming solutions that are free and open source, as will lead to the growth and adoption of precision farming solutions in the long run.

Combining epidemiology and economics to assess control of a viral endemic animal disease: Porcine Reproductive and Respiratory Syndrome (PRRS).

Porcine reproductive and respiratory syndrome (PRRS) is an extremely contagious disease that causes great damage to the U.S. pork industry. PRRS is not subject to official control in the U.S., but most producers adopt control strategies, including vaccination. However, the PRRS virus mutates frequently, facilitating its ability to infect even vaccinated animals. In this paper we analyze how increased vaccination on sow farms reduces PRRS losses and when vaccination is profitable. We develop a SIR model to simulate the spread of an outbreak between and within swine farms located in a region of Minnesota. Then, we estimate economic losses due to PRRS and calculate the benefits of vaccination. We find that increased vaccination of sow farms increases the private profitability of vaccination, and also transmits positive externalities to farms that do not vaccinate. Although vaccination reduces industry losses, a low to moderate vaccine efficacy implies that large PRRS losses remain, even on vaccinated farms. Our approach provides useful insight into the dynamics of an endemic animal disease and the benefits of different vaccination regimens.

Manifestation of SARS-CoV-2 Infections in Mink Related to Host-, Virus- and Farm-Associated Factors, The Netherlands 2020.

SARS-CoV-2 outbreaks on 69 Dutch mink farms in 2020 were studied to identify risk factors for virus introduction and transmission and to improve surveillance and containment measures. Clinical signs, laboratory test results, and epidemiological aspects were investigated, such as the date and reason of suspicion, housing, farm size and distances, human contact structure, biosecurity measures, and presence of wildlife, pets, pests, and manure management. On seven farms, extensive random sampling was performed, and age, coat color, sex, and clinical signs were recorded. Mild to severe respiratory signs and general diseases such as apathy, reduced feed intake, and increased mortality were detected on 62/69 farms. Throat swabs were more likely to result in virus detection than rectal swabs. Clinical signs differed between virus clusters and were more severe for dark-colored mink, males, and animals infected later during the year. Geographical clustering was found for one virus cluster. Shared personnel could explain some cases, but other transmission routes explaining farm-to-farm spread were not elucidated. An early warning surveillance system, strict biosecurity measures, and a (temporary) ban on mink farming and vaccinating animals and humans can contribute to reducing the risks of the virus spreading and acquisition of potential mutations relevant to human and animal health.

SARS-CoV-2 in a Mink Farm in Italy: Case Description, Molecular and Serological Diagnosis by Comparing Different Tests.

This study described a SARS-CoV-2 infection in minks on an Italian farm. Surveillance was performed based on clinical examination and a collection of 1879 swabs and 74 sera from dead and live animals. The farm was placed under surveillance for 4.5 months, from the end of July 2020, when a man working on the farm tested positive by RT-PCR, till mid-December 2020 when all the animals were sacrificed. Clinical examination revealed no clinical signs or increased mortality rates attributable to SARS-CoV-2, while diagnostic tests detected only four weak PCR-positive samples, but 100% of sera were positive for SARS-CoV-2 anti-S antibodies. The phylogenetic analysis of two SARS-CoV-2 sequences from two minks and the sequence of the worker showed that they belonged to different clades. It could be therefore assumed that two distinct introductions of the virus occurred on the farm, and that the first introduction probably occurred before the start of the surveillance period. From the data collected, and especially from the detection of specific antibodies through the combination of different tests, it can be postulated that syndromic surveillance combined with genome detection by PCR may not be sufficient to achieve a diagnosis in asymptomatic animals. In particular, the serological approach, especially when using tests directed towards the S protein, may be useful for improving the traceability of virus circulation in similar environments.

Point-of-Care Diagnostics for Farm Animal Diseases: From Biosensors to Integrated Lab-on-Chip Devices.

Zoonoses and animal diseases threaten human health and livestock biosecurity and productivity. Currently, laboratory confirmation of animal disease outbreaks requires centralized laboratories and trained personnel; it is expensive and time-consuming, and it often does not coincide with the onset or progress of diseases. Point-of-care (POC) diagnostics are rapid, simple, and cost-effective devices and tests, that can be directly applied on field for the detection of animal pathogens. The development of POC diagnostics for use in human medicine has displayed remarkable progress. Nevertheless, animal POC testing has not yet unfolded its full potential. POC devices and tests for animal diseases face many challenges, such as insufficient validation, simplicity, and portability. Emerging technologies and advanced materials are expected to overcome some of these challenges and could popularize animal POC testing. This review aims to: (i) present the main concepts and formats of POC devices and tests, such as lateral flow assays and lab-on-chip devices; (ii) summarize the mode of operation and recent advances in biosensor and POC devices for the detection of farm animal diseases; (iii) present some of the regulatory aspects of POC commercialization in the EU, USA, and Japan; and (iv) summarize the challenges and future perspectives of animal POC testing.

Children, Work, and Safety on the Farm during COVID-19: A Harder Juggling Act.

OBJECTIVES: Measures to curb the spread of COVID-19 in the Spring of 2020 immediately raised concerns among farm safety experts about the increase in children's risk exposure due to changes in childcare and schooling arrangements. The goal of this study is to understand how farm parents were taking care of their children in the early months of COVID-19. METHODS: I conducted univariate and inductive content analysis on survey data from 134 farm parents from 38 U.S. states to understand. RESULTS: My findings overall confirm experts' predictions. The move to distance learning for about three-quarter of respondents with school-age children and changes in childcare arrangements for over half of those with pre-school-age children led respondents to contend with fewer options and added responsibilities. Most frequently used adaptation strategies reflected lower reliance on the traditionally important social networks, a desire to preserve household income, and greater involvement of children on the farm. As a result, taking care of their children became harder for more than half of respondents with likely repercussions on children's exposure to risk, parents' well-being, and on the farm business. CONCLUSION: The empirical insights of this study provide descriptive baseline and contextual data for future research on the impact of COVID-19. The conceptual insights expand the farm safety literature by illustrating the need to study underappreciated structural factors shaping how farm parents juggle children with their professional obligations. Finally, findings around the complexity of raising children and connections to farm productivity and farm safety highlight the importance of considering farm women's well-being alongside the safety of their children.