Empirical modeling of agricultural climate risk.

Effective policies for adaptation to climate change require understanding how impacts are related to exposures and vulnerability, the dimensions of the climate system that will change most and where human impacts will be most draconian, and the institutions best suited to respond. Here, we propose a simple method for more credibly pairing empirical statistical damage estimates derived from recent weather and outcome observations with projected future climate changes and proposed responses. We first analyze agricultural production and loan repayment data from Brazil to understand vulnerability to historical variation in the more predictable components of temperature and rainfall (trend and seasonality) as well as to shocks (both local and over larger spatial scales). This decomposed weather variation over the past two decades explains over 50% of the yield variation in major Brazilian crops and, critically, can be constructed in the same way for future climate projections. Combining our estimates with bias-corrected downscaled climate simulations for Brazil, we find increased variation in yields and revenues (including more bad years and worse outcomes) and higher agricultural loan default at midcentury. Results in this context point to two particularly acute dimensions of vulnerability: Intensified seasonality and local idiosyncratic shocks both contribute to worsening outcomes, along with a reduced capacity for spatially correlated ("covariate") shocks to ameliorate these effects through prices. These findings suggest that resilience strategies should focus on institutions such as water storage, financial services, and reinsurance.

Age-Dependent Variations in Kawasaki Disease Incidence in Japan.

Importance: The etiology of Kawasaki disease (KD) remains elusive, with immunologic and epidemiologic data suggesting different triggers in individuals who are genetically susceptible. KD remains the most common cause of acquired heart disease in pediatric patients, and Japan is the country of highest incidence, with an increasing number of cases. Objective: To investigate whether an analysis of the epidemiologic KD record in Japan stratified by age and prefecture (subregion) may yield new clues regarding mechanisms of exposure to etiologic agents associated with KD. Design, Setting, and Participants: This cross-sectional study was conducted using a dataset of patients with KD with detailed information on location and age at onset created through nationwide surveys of hospitals caring for pediatric patients with KD throughout Japan. Pediatric patients hospitalized in Japan for KD from 1970 to 2020 were included. Data were analyzed from January 2022 to January 2024. Exposure: Pediatric patients with KD. Main Outcomes and Measures: The KD dataset was analyzed by patient age (infants [aged <6 months], toddlers [aged 6 to <24 months], children aged 2 years [aged 24 to <36 months], and children and adolescents aged 3 years or older [aged ≥36 months]), with investigations of seasonal cycles, interannual variations, and correlations across regions. Results: Among 422 528 pediatric patients (243 803 males [57.7%] and 178 732 females [42.3%]; median [IQR] age, 23.69 [11.96-42.65] months), infants, toddlers, and patients aged 3 years or older exhibited different rates of increase in KD incidence, seasonality, and degrees of coherence of seasonality across prefectures. Although the mean (SD) incidence of KD among infants remained relatively stable over the past 30 years compared with older patients (1.00 [0.07] in 1987-1992 to 2.05 [0.11] in 2011-2016), the mean (SD) incidence rate for children and adolescents aged 3 years or older increased 5.2-fold, from 1.00 (0.08) in 1987 to 1992 to 5.17 (0.46) in 2014 to 2019. Patients aged 3 years or older saw a reduction in mean (SD) incidence, from peaks of 5.71 (0.01) in October 2014 through June 2015 and July 2018 through March 2019 to 4.69 (0.11) in 2016 to 2017 (17.8% reduction) not seen in younger children. The seasonal cycle varied by age group; for example, mean (SD) incidence peaked in July and August (5.63 [0.07] cases/100 000 individuals) for infants and in December and January (4.67 [0.13] cases/100 000 individuals) for toddlers. Mean (SD) incidence changed dramatically for toddlers beginning in the early 2010s; for example, the normalized mean (SD) incidence among toddlers for October was 0.74 (0.03) in 1992 to 1995 and 1.10 (0.01) in 2016 to 2019. Across Japan, the seasonal cycle of KD incidence of older children and adolescents exhibited mean (SD) correlation coefficients between prefectures as high as 0.78 (0.14) for prefecture 14 among patients aged 3 years or older, while that of infants was much less (highest mean [SD] correlation coefficient, 0.43 [0.23]). Conclusions and Relevance: This study found distinct temporal signatures and changing spatial consistency of KD incidence across age groups, suggesting different age-related mechanisms of exposure. Some results suggested that social factors may modulate exposure to etiologic agents of KD; however, the increase in KD incidence in older children coupled with the correlation across prefectures of KD incidence suggest that the intensity of an environmental exposure that triggers KD in this age group may have increased over time.

Air quality equity in US climate policy.

The United States government has indicated a desire to advance environmental justice through climate policy. As fossil fuel combustion produces both conventional pollutants and greenhouse gas (GHG) emissions, climate mitigation strategies may provide an opportunity to address historical inequities in air pollution exposure. To test the impact of climate policy implementation choices on air quality equity, we develop a broad range of GHG reduction scenarios that are each consistent with the US Paris Accord target and model the resulting air pollution changes. Using idealized decision criteria, we show that least cost and income-based emission reductions can exacerbate air pollution disparities for communities of color. With a suite of randomized experiments that facilitates exploration of a wider climate policy decision space, we show that disparities largely persist despite declines in average pollution exposure, but that reducing transportation emissions has the most potential to reduce racial inequities.

Geographically resolved social cost of anthropogenic emissions accounting for both direct and climate-mediated effects.

The magnitude and distribution of physical and societal impacts from long-lived greenhouse gases are insensitive to the emission source location; the same is not true for major coemitted short-lived pollutants such as aerosols. Here, we combine novel global climate model simulations with established response functions to show that a given aerosol emission from different regions produces divergent air quality and climate changes and associated human system impacts, both locally and globally. The marginal global damages to infant mortality, crop productivity, and economic growth from aerosol emissions and their climate effects differ by more than an order of magnitude depending on source region, with certain regions creating global external climate changes and impacts much larger than those felt locally. The complex distributions of aerosol-driven societal impacts emerge from geographically distinct and region-specific aerosol-climate interactions, estimation of which is enabled by the full Earth System Modeling Framework used here.

Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US.

Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM2.5 concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM2.5 over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM2.5. Smoke contributions to daily PM2.5 concentrations have increased by up to 5 µg/m3 in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM2.5 above 100 µg/m3 per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.

Exposures and behavioural responses to wildfire smoke.

Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM2.5) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.

Globally ubiquitous negative effects of nitrogen dioxide on crop growth.

Nitrogen oxides (NOx) are among the most widely emitted pollutants in the world, yet their impacts on agriculture remain poorly known. NOx can directly damage crop cells and indirectly affect growth by promoting ozone (O3) and aerosol formation. We use satellite measures of both crop greenness and NOx during 2018-2020 to evaluate crop impacts for five major agricultural regions. We find consistent negative associations between NO2 and greenness across regions and seasons. These effects are strongest in conditions where O3 formation is NOx limited but remain significant even in locations where this pathway is muted, suggesting a role for direct NOx damage. Using simple counterfactuals and leveraging published relationships between greenness and growth, we estimate that reducing NOx levels to the current fifth percentile in each region would raise yields by ~25% for winter crops in China, ~15% for summer crops in China, and up to 10% in other regions.

Epidemiological and Clinical Features of Kawasaki Disease During the COVID-19 Pandemic in the United States.

Importance: Public health measures implemented during the COVID-19 pandemic had widespread effects on population behaviors, transmission of infectious diseases, and exposures to environmental pollutants. This provided an opportunity to study how these factors potentially influenced the incidence of Kawasaki disease (KD), a self-limited pediatric vasculitis of unknown etiology. Objectives: To examine the change in KD incidence across the United States and evaluate whether public health measures affected the prevalence of KD. Design, Setting, and Participants: This multicenter cohort study included consecutive, unselected patients with KD who were diagnosed between January 1, 2018, and December 31, 2020 (multicenter cohort with 28 pediatric centers), and a detailed analysis of patients with KD who were diagnosed between January 1, 2002, and November 15, 2021 (Rady Children's Hospital San Diego [RCHSD]). Main Outcomes and Measures: For the multicenter cohort, the date of fever onset for each patient with KD was collected. For RCHSD, detailed demographic and clinical data as well as publicly available, anonymized mobile phone data and median household income by census block group were collected. The study hypothesis was that public health measures undertaken during the pandemic would reduce exposure to the airborne trigger(s) of KD and that communities with high shelter-in-place compliance would experience the greatest decrease in KD incidence. Results: A total of 2461 KD cases were included in the multicenter study (2018: 894; 2019: 905; 2020: 646), and 1461 cases (median [IQR] age, 2.8 years [1.4-4.9 years]; 900 [61.6%] males; 220 [15.1%] Asian, 512 [35.0%] Hispanic, and 338 [23.1%] White children) from RCHSD between 2002 and 2021 were also included. The 28.2% decline in KD cases nationally during 2020 (646 cases) compared with 2018 (894 cases) and 2019 (905 cases) was uneven across the United States. For RCHSD, there was a disproportionate decline in KD cases in 2020 to 2021 compared with the mean (SD) number of cases in earlier years for children aged 1 to 5 years (22 vs 44.9 [9.9]; P = .02), male children (21 vs 47.6 [10.0]; P = .01), and Asian children (4 vs 11.8 [4.4]; P = .046). Mobility data did not suggest that shelter-in-place measures were associated with the number of KD cases. Clinical features including strawberry tongue, enlarged cervical lymph node, and subacute periungual desquamation were decreased during 2020 compared with the baseline period (strawberry tongue: 39% vs 63%; P = .04; enlarged lymph node: 21% vs 32%; P = .09; periungual desquamation: 47% vs 58%; P = .16). School closures, masking mandates, decreased ambient pollution, and decreased circulation of respiratory viruses all overlapped to different extents with the period of decreased KD cases. KD in San Diego rebounded in the spring of 2021, coincident with lifting of mask mandates. Conclusions and Relevance: In this study of epidemiological and clinical features of KD during the COVID-19 pandemic in the United States, KD cases fell and remained low during the period of masking and school closure. Mobility data indicated that differential intensity of sheltering in place was not associated with KD incidence. These findings suggest that social behavior is associated with exposure to the agent(s) that trigger KD and are consistent with a respiratory portal of entry for the agent(s).

Land-use emissions embodied in international trade.

International trade separates consumption of goods from related environmental impacts, including greenhouse gas emissions from agriculture and land-use change (together referred to as "land-use emissions"). Through use of new emissions estimates and a multiregional input-output model, we evaluated land-use emissions embodied in global trade from 2004 to 2017. Annually, 27% of land-use emissions and 22% of agricultural land are related to agricultural products ultimately consumed in a different region from where they were produced. Roughly three-quarters of embodied emissions are from land-use change, with the largest transfers from lower-income countries such as Brazil, Indonesia, and Argentina to more industrialized regions such as Europe, the United States, and China. Mitigation of global land-use emissions and sustainable development may thus depend on improving the transparency of supply chains.

Temporal clustering of Kawasaki disease cases around the world.

In a single-site study (San Diego, CA, USA), we previously showed that Kawasaki Disease (KD) cases cluster temporally in bursts of approximately 7 days. These clusters occurred more often than would be expected at random even after accounting for long-term trends and seasonality. This finding raised the question of whether other locations around the world experience similar temporal clusters of KD that might offer clues to disease etiology. Here we combine data from San Diego and nine additional sites around the world with hospitals that care for large numbers of KD patients, as well as two multi-hospital catchment regions. We found that across these sites, KD cases clustered at short time scales and there were anomalously long quiet periods with no cases. Both of these phenomena occurred more often than would be expected given local trends and seasonality. Additionally, we found unusually frequent temporal overlaps of KD clusters and quiet periods between pairs of sites. These findings suggest that regional and planetary range environmental influences create periods of higher or lower exposure to KD triggers that may offer clues to the etiology of KD.

Improving production and quality of life for smallholder farmers through a climate resilience program: An experience in the Brazilian Sertão.

We use a combination of economic and wellbeing metrics to evaluate the impacts of a climate resilience program designed for family farmers in the semiarid region of Brazil. Most family farmers in the region are on the verge of income and food insufficiency, both of which are exacerbated in prolonged periods of droughts. The program assisted farmers in their milk and sheepmeat production, implementing a set of climate-smart production practices and locally-adapted technologies. We find that the program under evaluation had substantive and significant impacts on production practices, land management, and quality of life in general, using several different quasi-experimental strategies to estimate the average treatment effect on the treated farmers. We highlight the strengths and limitations of each evaluation strategy and how the set of analyses and outcome indicators complement each other. The evaluation provides valuable insights into the economic and environmental sustainability of family farming in semiarid regions, which are under growing pressure from climate change and environmental degradation worldwide.

Characterization of Groundwater Recharge and Flow in California's San Joaquin Valley From InSAR-Observed Surface Deformation.

Surface deformation in California's Central Valley (CV) has long been linked to changes in groundwater storage. Recent advances in remote sensing have enabled the mapping of CV deformation and associated changes in groundwater resources at increasingly higher spatiotemporal resolution. Here, we use interferometric synthetic aperture radar (InSAR) from the Sentinel-1 missions, augmented by continuous Global Positioning System (cGPS) positioning, to characterize the surface deformation of the San Joaquin Valley (SJV, southern two-thirds of the CV) for consecutive dry (2016) and wet (2017) water years. We separate trends and seasonal oscillations in deformation time series and interpret them in the context of surface and groundwater hydrology. We find that subsidence rates in 2016 (mean -42.0 mm/yr; peak -345 mm/yr) are twice that in 2017 (mean -20.4 mm/yr; peak -177 mm/yr), consistent with increased groundwater pumping in 2016 to offset the loss of surface-water deliveries. Locations of greatest subsidence migrated outwards from the valley axis in the wetter 2017 water year, possibly reflecting a surplus of surface-water supplies in the lowest portions of the SJV. Patterns in the amplitude of seasonal deformation and the timing of peak seasonal uplift reveal entry points and potential pathways for groundwater recharge into the SJV and subsequent groundwater flow within the aquifer. This study provides novel insight into the SJV aquifer system that can be used to constrain groundwater flow and subsidence models, which has relevance to groundwater management in the context of California's 2014 Sustainable Groundwater Management Act (SGMA).

Using Crowd-Sourced Data to Assess the Temporal and Spatial Relationship between Indoor and Outdoor Particulate Matter.

Using hourly measures across a full year of crowd-sourced data from over 1000 indoor and outdoor pollution monitors in the state of California, we explore the temporal and spatial relationship between outdoor and indoor particulate matter (PM) concentrations for different particle sizes. The scale of this study offers new insight into both average penetration rates and drivers of heterogeneity in the outdoor-indoor relationship. We find that an increase in the daily outdoor PM concentration of 10% leads to an average increase of 4.2-6.1% in indoor concentrations. The penetration of outdoor particles to the indoor environment occurs rapidly and almost entirely within 5 h. We also provide evidence showing that penetration rates are associated with building age and climatic conditions in the vicinity of the monitor. Since people spend a substantial amount of each day indoors, our findings fill a critical knowledge gap and have significant implications for government policies to improve public health through reductions in exposure to ambient air pollution.

Global and regional drivers of land-use emissions in 1961-2017.

Historically, human uses of land have transformed and fragmented ecosystems1,2, degraded biodiversity3,4, disrupted carbon and nitrogen cycles5,6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere7,8. However, in contrast to fossil-fuel carbon dioxide (CO2) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO2-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO2-equivalent per decade to 14.6 gigatonnes CO2-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO2-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge-for example, on the role of population and economic growth and dietary choice-but provide additional insight into regional and sectoral trends.

The changing risk and burden of wildfire in the United States.

Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM2.5 (particulate matter with diameter <2.5 µm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change-but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.

Temperature-driven harvest decisions amplify US winter wheat loss under climate warming.

Most studies quantifying the impacts of climatic variability and warming on crop production have focused on yields and have overlooked potential areal and frequency responses, potentially biasing future projections of food security in a warming world. Here we analyze US winter wheat production from 1970 to 2017 and find that harvest area ratio (harvested area/planted area, HAR) has declined while yields have risen, standing in stark contrast to other US staple crops. Although lower profitability due to declining wheat prices appears to explain the HAR trend, fluctuating wheat yields-largely explained by temperature exposure-drive the interannual variation of HAR. Our analysis suggests that warming-induced declines in HAR are comparable in magnitude to heat-related yield losses, and lower wheat prices amplify the sensitivity of HAR to warming and yield variation. Although irrigation mitigates some temperature-driven yield effects, it does little to change HAR, likely due to infrastructure cost and limited influence on relative profitability. Our results suggest that an accurate quantification of climate impacts on crop production must account for harvested area response, and that future adaptation strategies should not only target crop choice and management but also harvest incentives.

Temporal Clusters of Kawasaki Disease Cases Share Distinct Phenotypes That Suggest Response to Diverse Triggers.

OBJECTIVE: To test the hypothesis that cases of Kawasaki disease within a temporal cluster have a similar pattern of host response that is distinct from cases of Kawasaki disease in different observed clusters and randomly constructed clusters. STUDY DESIGN: We designed a case-control study to analyze 47 clusters derived from 1332 patients with Kawasaki disease over a 17-year period (2002-2019) from a single clinical site and compared the cluster characteristics with those of 2 control groups of synthetic Kawasaki disease clusters. We defined a "true" Kawasaki disease cluster as at least 5 patients within a 7-day moving window. The observed and synthetic Kawasaki disease clusters were compared with respect to demographic and clinical characteristics and median values for standard laboratory data using univariate analysis and a multivariate, rotated empirical orthogonal function analysis. RESULTS: In a univariate analysis, the median values for age, coronary artery z-score, white blood cell count, erythrocyte sedimentation rate, C-reactive protein, and age-adjusted hemoglobin for several of the true Kawasaki disease clusters exceeded the 95th percentile for the 2 synthetic clusters. REOF analyses revealed distinct patterns of demographic and clinical measures within clusters. CONCLUSIONS: Cases of Kawasaki disease within a cluster were more similar with respect to demographic and clinical features and levels of inflammation than would be expected by chance. These observations suggest that different triggers and/or different intensities of exposures result in clusters of cases of Kawasaki disease that share a similar response pattern. Analyzing cases within clusters or cases who share demographic and clinical features may lead to new insights into the etiology of Kawasaki disease.

The impact of a Solar Market Garden programme on dietary diversity, women's nutritional status and micronutrient levels in Kalalé district of northern Benin.

OBJECTIVE: To examine the impacts of a Solar Market Garden 1-year solar-powered drip irrigation (SMG) programme in Kalalé district of northern Benin on mothers' nutritional status and micronutrient levels. DESIGN: Using a quasi-experimental design, sixteen villages were assigned to four groups: (i) SMG women's groups (WG); (ii) comparison WG; (iii) SMG non-WG (NWG); and (iv) comparison NWG. Difference-in-differences (DID) estimates were used to assess impacts on mothers' food consumption, diversity, BMI, prevalence of underweight (BMI < 18·5 kg/m2) and anaemia, and deficiencies of iron (ID) and vitamin A (VAD). SETTING: Kalalé district, northern Benin. PARTICIPANTS: Non-pregnant mothers aged 15-49 years (n 1737). RESULTS: The SMG programme significantly increased mothers' intake of vegetables (DID = 25·31 percentage points (pp); P < 0·01), dietary diversity (DID = 0·74; P < 0·01) and marginally increased their intake of flesh foods (DID = 10·14 pp; P < 0·1). Mean BMI was significantly increased among SMG WG compared with the other three groups (DID = 0·44 kg/m2; P < 0·05). The SMG programme also significantly decreased the prevalence of anaemia (DID = 12·86 pp; P < 0·01) but no impacts were found for the prevalence of underweight, ID and VAD. CONCLUSIONS: Improving mothers' dietary intake and anaemia prevalence supports the need to integrate gender-based agriculture to improve nutritional status. However, it may take more than a year, and additional nutrition and health programmes, to impact the prevalence of maternal underweight, ID and VAD.

Author Correction: Clustering and climate associations of Kawasaki Disease in San Diego County suggest environmental triggers.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Clustering and climate associations of Kawasaki Disease in San Diego County suggest environmental triggers.

Kawasaki Disease (KD) is the most common cause of pediatric acquired heart disease, but its etiology remains unknown. We examined 1164 cases of KD treated at a regional children's hospital in San Diego over a period of 15 years and uncovered novel structure to disease incidence. KD cases showed a well-defined seasonal variability, but also clustered temporally at much shorter time scales (days to weeks), and spatiotemporally on time scales of up to 10 days and spatial scales of 10-100 km. Temporal clusters of KD cases were associated with strongly significant regional-scale air temperature anomalies and consistent larger-scale atmospheric circulation patterns. Gene expression analysis further revealed a natural partitioning of KD patients into distinct groups based on their gene expression pattern, and that the different groups were associated with certain clinical characteristics that also exhibit temporal autocorrelation. Our data suggest that one or more environmental triggers exist, and that episodic exposures are modulated at least in part by regional weather conditions. We propose that characterization of the environmental factors that trigger KD in genetically susceptible children should focus on aerosols inhaled by patients who share common disease characteristics.