[Evaluation of Non-Pharmaceutical Interventions for Reducing Contact Rate in COVID-19 Pandemic: R0 Estimation and Modeling for Istanbul]. / COVID-19 Salgininin Kontrolünde Ilaç Disi Tedbirlerden Temas Sayisini Azaltmaya Yönelik Kisitlamalarin Etkinliginin Degerlendirilmesi: R0 Hesaplamasi ve Modelleme Çalismasi ile Istanbul Örnegi.

After the declaration of the coronavirus-2019 (COVID-19) pandemic and the detection of the COVID-19 case in Turkey, a series of non-pharmaceutical measures were implemented to reduce the number of contacts at the national level. The aim of this study was to determine the change in the epidemic reproduction rate (R0) with non-pharmaceutical interventions including curfews starting with the first reported case in Istanbul and to evaluate the effectiveness of interventions by estimating the number of cases and deaths using a dynamic compartmental model. While keeping transmission probability (beta) as 3% and incubation period as seven days, we developed five scenarios that represented nonpharmaceutical interventions The first scenario was "if nothing was done" and the last scenario was "curfew". The contact matrix of 16 age-groups created by Prem et al. was used in the study as the contact matrix of "if nothing was done" as scenario 1. For all other scenarios (2-5) contact matrices assumptions were created and R0 values were calculated for the whole of Istanbul according to age groups for all five scenarios. For each scenario, "the number of cases and COVID-related deaths" for one year from the day the first case was detected were calculated with the mathematical modeling method. In the absence of any intervention, R0 value was estimated as 2.86 in Istanbul. Among age-groups, the largest R0 value was observed in ages 15-19, 10-14, 5-9, 20-24 and the values were 5.22, 4.37, 3.32, and 3.33; respectively. Due to school closings and flexible work hours, R0 values decreased to 2.02, 1.84, 1.63 and 1.85 in the same age-groups. With the addition of a curfew for the population under the age of 20 to the above measures, the R0 values for all age groups were reduced to less than one. When R0 values for Istanbul was 2.86 and 1.55 based on our model results, the number of cases and deaths per year were determined as approximately 14 million and 2 million and 2.5 million and 327.000, respectively. School closures were determined as the most effective non-pharmaceutical intervention. Non-pharmaceutical measures with the addition of curfews under the age of 20 and over the age of 65 to the school closings and flexible working hours were identified as effective methods in controlling the COVID-19 epidemic in Istanbul. While the results of this study may not reflect real life data, it has the potential of helping public health policy makers to decide on which non-pharmaceutical interventions are the most effective.

Association between physician adoption of a new oral anti-diabetic medication and Medicare and Medicaid drug spending.

BACKGROUND: In the United States, there is well-documented regional variation in prescription drug spending. However, the specific role of physician adoption of brand name drugs on the variation in patient-level prescription drug spending is still being investigated across a multitude of drug classes. Our study aims to add to the literature by determining the association between physician adoption of a first-in-class anti-diabetic (AD) drug, sitagliptin, and AD drug spending in the Medicare and Medicaid populations in Pennsylvania. METHODS: We obtained physician-level data from QuintilesIMS Xponent™ database for Pennsylvania and constructed county-level measures of time to adoption and share of physicians adopting sitagliptin in its first year post-introduction. We additionally measured total AD drug spending for all Medicare fee-for-service and Part D enrollees (N = 125,264) and all Medicaid (N = 50,836) enrollees with type II diabetes in Pennsylvania for 2011. Finite mixture model regression, adjusting for patient socio-demographic/clinical characteristics, was used to examine the association between physician adoption of sitagliptin and AD drug spending. RESULTS: Physician adoption of sitagliptin varied from 44 to 99% across the state's 67 counties. Average per capita AD spending was $1340 (SD $1764) in Medicare and $1291 (SD $1881) in Medicaid. A 10% increase in the share of physicians adopting sitagliptin in a county was associated with a 3.5% (95% CI: 2.0-4.9) and 5.3% (95% CI: 0.3-10.3) increase in drug spending for the Medicare and Medicaid populations, respectively. CONCLUSIONS: In a medication market with many choices, county-level adoption of sitagliptin was positively associated with AD spending in Medicare and Medicaid, two programs with different approaches to formulary management.

Ossicular chain erosion in chronic otitis media patients with cholesteatoma or granulation tissue or without those: analysis of 915 cases.

PURPOSE: The aim of this study was to evaluate the ossicular chain erosions (OCE) in chronic otitis media patients with cholesteatoma (COM-C) or without cholesteatoma (COM). MATERIALS AND METHODS: The OCE and preoperative hearing levels of a total of 915 patients were evaluated retrospectively. Patients were divided into three groups. Of the 915 patients, 615 (67.2%) had COM, 234 (25.6%) had COM-C, and 66 (7.2%) had chronic otitis media with granulation tissue (COM-G). RESULTS: OCE was found in 291 (31.8%) of 915 patients. OCE was found in 192 (82%) of 234 patients with COM-C, 21 (31.8%) of 66 patients with COM-G, and 78 (12.7%) of 615 patients with COM. CONCLUSION: The most commonly seen OCE was incus erosion, followed by stapes and malleus erosions. The results of this study show that there are more OCE in the COM-C group than in the COM-G and COM groups. To our knowledge, this study has the widest patient population in the literature focused on the OCE relation with COM, COM-C, and COM-G and its effect on the preoperative hearing level.

Who Were the Early Adopters of Dabigatran?: An Application of Group-based Trajectory Models.

BACKGROUND: Variation in physician adoption of new medications is poorly understood. Traditional approaches (eg, measuring time to first prescription) may mask substantial heterogeneity in technology adoption. OBJECTIVE: Apply group-based trajectory models to examine the physician adoption of dabigratran, a novel anticoagulant. METHODS: A retrospective cohort study using prescribing data from IMS Xponent™ on all Pennsylvania physicians regularly prescribing anticoagulants (n=3911) and data on their characteristics from the American Medical Association Masterfile. We examined time to first dabigatran prescription and group-based trajectory models to identify adoption trajectories in the first 15 months. Factors associated with rapid adoption were examined using multivariate logistic regressions. OUTCOMES: Trajectories of monthly share of oral anticoagulant prescriptions for dabigatran. RESULTS: We identified 5 distinct adoption trajectories: 3.7% rapidly and extensively adopted dabigatran (adopting in ≤3 mo with 45% of prescriptions) and 13.4% were rapid and moderate adopters (≤3 mo with 20% share). Two groups accounting for 21.6% and 16.1% of physicians, respectively, were slower to adopt (6-10 mo post-introduction) and dabigatran accounted for <10% share. Nearly half (45.2%) of anticoagulant prescribers did not adopt dabigatran. Cardiologists were much more likely than primary care physicians to rapidly adopt [odds ratio (OR)=12.2; 95% confidence interval (CI), 9.27-16.1] as were younger prescribers (age 36-45 y: OR=1.49, 95% CI, 1.13-1.95; age 46-55: OR=1.34, 95% CI, 1.07-1.69 vs. >55 y). CONCLUSIONS: Trajectories of physician adoption of dabigatran were highly variable with significant differences across specialties. Heterogeneity in physician adoption has potential implications for the cost and effectiveness of treatment.

FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

BACKGROUND: Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. RESULTS: FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. CONCLUSIONS: State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

Global maize trade and food security: implications from a social network model.

In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.N. Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, whereas Japan and the Republic of Korea are the largest maize importers. In particular, the star-shaped cluster of the network that represents U.S. maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which U.S. maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide.

Evaluation of the Association between Lumbar Spinal Stenosis and Lumbar Subcutaneous Fat Tissue Thickness by MRI: A Novel Perspective.

OBJECTIVE: To evaluate whether lumbar subcutaneous fat tissue thickness (LSFTT) on midsagittal magnetic resonance imaging (MRI) is associated with lumbar spinal stenosis (LSS). STUDY DESIGN: Observational cross-sectional study. PLACE AND DURATION OF STUDY: Department of Radiology and Neurosurgery, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey between January 2018 and December 2020. METHODOLOGY: The study group included 79 patients, who had undergone surgery for lumbar spinal stenosis. The control group included MRI scans of 80 individuals without lumbar spinal stenosis. Association between LSFTT and LSS was analysed through a comparison of both the groups. RESULTS: The agreement between the two observers was found to be very good agreement with a two-way mixed intra-class correlation coefficient of 0.986 or higher (p <0.001). There was statistically significant differences between the LSS and non-LSS groups for both L5-S1 and L4-5 level measurements, p=0.001, and p=0.004, respectively. L5-S1 level measurements in the LSS group showed 29% increase in average with respect to the non-LSS group; and in L4-L5 level measurements, the increase was 40% in median. Females exhibited significantly higher values in both levels, (p <0.001 and p <0.001, respectively). CONCLUSIONS: Lumbar subcutaneous fat tissue thickness is significantly associated with lumbar spinal stenosis. Measuring LSFTT on mid-sagittal MRI is an easily applicable, reproducible alternative method for predicting LSS. Key Word: Lumbar, Spinal canal, Stenosis, Subcutaneous fat tissue, Magnetic resonance imaging.

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Modelling disease outbreaks in realistic urban social networks.

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Anterior third ventricular height and infundibulochiasmatic angle: two novel measurements to predict clinical success of endoscopic third ventriculostomy in the early postoperative period.

OBJECTIVE: The authors sought to develop a set of parameters that reliably predict the clinical success of endoscopic third ventriculostomy (ETV) when assessed before and after the operation, and to establish a plan for MRI follow-up after this procedure. METHODS: This retrospective study involved 77 patients who had undergone 78 ETV procedures for obstructive hydrocephalus between 2010 and 2015. Constructive interference in steady-state (CISS) MRI evaluations before and after ETV were reviewed, and 4 parameters were measured. Two well-known standard parameters, fronto-occipital horn ratio (FOHR) and third ventricular index (TVI), and 2 newly defined parameters, infundibulochiasmatic (IC) angle and anterior third ventricular height (TVH), were measured in this study. Associations between preoperative measurements of and postoperative changes in the 4 variables and the clinical success of ETV were analyzed. RESULTS: Of the 78 ETV procedures, 70 (89.7%) were successful and 8 (10.3%) failed. On the preoperative MR images, the mean IC angle and anterior TVH were significantly larger in the successful procedures. On the 24-hour postoperative MR images of the successful procedures, the mean IC angle declined significantly from 114.2° to 94.6° (p < 0.05) and the mean anterior TVH declined significantly from 15 to 11.2 mm (p < 0.05). The mean percentage reduction of the IC angle was 17.1%, and that of the anterior TVH was 25.5% (both p < 0.05). On the 1-month MR images of the successful procedures, the mean IC angle declined significantly from 94.6° to 84.2° (p < 0.05) and the mean anterior TVH declined significantly from 11.2 to 9.3 mm (p < 0.05). The mean percentage reductions in IC angle (11%) and anterior TVH (16.9%) remained significant at this time point but were smaller than those observed at 24 hours. The 6-month and 1-year postoperative MR images of the successful group showed no significant changes in mean IC angle or mean anterior TVH. Regarding the unsuccessful procedures, there were no significant changes observed in IC angle or anterior TVH at any of the time points studied. Reduction of IC angle and reduction of anterior TVH on 24-hour postoperative MR images were significantly associated with successful ETV. However, no clinically significant association was found between FOHR, TVI, and ETV success. CONCLUSIONS: Assessing the IC angle and anterior TVH on preoperative and 24-hour postoperative MR images is useful for predicting the clinical success of ETV. These 2 measurements could also be valuable as radiological follow-up parameters.

Influence of peer networks on physician adoption of new drugs.

Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians' own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications. We constructed 4 types of peer networks based on shared Medicare and Medicaid patients, medical group affiliation, hospital affiliation, and medical school/residency training. Instrumental variables analysis was used to estimate the causal effect of peer adoption (fraction of peers in each network adopting the new drug) on physician adoption (prescribing at least the median number prescriptions within 15 months of the new drug's introduction). We illustrate how physician network position can inform targeting of interventions to physicians by computing a social multiplier. Dabigatran was adopted by 25.2%, sitagliptin by 24.5% and aliskiren by 8.3% of physicians. A 10-percentage point increase in peer adoption in the patient-sharing network led to a 5.90% (SE = 1.50%, p<0.001) increase in physician adoption of dabigatran, 8.32% (SE = 1.51%, p<0.001) increase in sitagliptin, and 7.84% increase in aliskiren adoption (SE = 2.93%, p<0.001). Peer effects through shared hospital affiliation were positive but not significant, and medical group and training network effects were not reliably estimated. Physicians in the top decile of patient-sharing network peers were estimated to have nearly 2-fold stronger influence on their peers' adoption compared to physicians in the top decile of prescribing volume. Limitations include lack of detailed clinical information and pharmaceutical promotion, variables which may influence physician adoption but which are unlikely to bias our peer effect estimates. Peer adoption, especially by those with whom physicians share patients, strongly influenced physician adoption of new drugs. Our study shows the potential for using information on physician peer networks to improve technology diffusion.

Patterns and predictors of physician adoption of new cardiovascular drugs.

BACKGROUND: Little is known about physicians' approaches to adopting new cardiovascular drugs and how adoption varies between drugs of differing novelty. METHODS: Using data on dispensed prescriptions from IMS Health's Xponent™ database, we created a cohort of all primary care physicians (PCPs) and cardiologists in Pennsylvania who regularly prescribed anticoagulants, antihypertensives and statins from 2007 to 2011. We examined prescribing of three new cardiovascular drugs of differing novelty: dabigatran, aliskiren and pitavastatin. Outcomes were rapid adoption of each new drug, defined by early and sustained monthly prescribing detected by group-based trajectory models, by physicians within the first 15 months of marketplace introduction. RESULTS: 5953 physicians regularly prescribed each drug class. The majority of physicians (63.8%) adopted zero new drugs in the first 15 months, 35.0% rapidly adopted one or two, and 1.2% rapidly adopted all three. Physicians were more likely to rapidly adopt the most novel drug, dabigatran (27.3%), than aliskiren (10.5%) or pitavastatin (8.0%). Physician specialty and sex were the most consistent predictors of adoption. Compared to PCPs, cardiologists were more likely to rapidly adopt dabigatran (Adjusted Odds Ratio 8.90, 95% confidence interval 7.42-10.67; P<0.001) aliskerin (2.05, CI 1.56-2.69; P<0.001) and pitavastatin (3.44, CI 2.60-4.57; P<0.001). Female physicians were less likely to adopt dabigatran (0.71, CI 0.59-0.85; P <0.001) and aliskiren (0.64, CI 0.49-0.83; P <0.001). CONCLUSIONS: Physicians vary in their prescribing of recently-introduced cardiovascular drugs. Though most physicians did not rapidly adopt any new cardiovascular drugs, drug novelty and cardiology training were associated with greater adoption.

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula.

OBJECTIVE: Assess Hurricane Sandy's impact on primary care providers' services in the Rockaways. METHODS: In-person surveys were conducted in 2014. A list of 46 health care sites in the area of interest was compiled and each site was called to offer participation in our survey. Respondents included physicians and practice administrators who remained familiar with Sandy-related operational challenges. RESULTS: Of the 40 sites that opted in, most had been in their current location for more than 10 years (73%) and were a small practice (1 or 2 physicians) before Hurricane Sandy (75%). All but 2 (95%) had to temporarily close or relocate. All sites experienced electrical problems that impacted landline, fax, and Internet. Less than one-quarter (n = 9) reported having a plan for continuity of services before Hurricane Sandy, and 43% reported having a plan poststorm. The majority (80%) did not report coordinating with other primary care stakeholders or receiving support from government agencies during the Sandy response. CONCLUSIONS: Hurricane Sandy significantly disrupted access to primary care in the Rockaways. Severe impact to site operations and infrastructure forced many practices to relocate. Greater emergency response and recovery planning is needed, including with government agencies, to minimize disruptions of access to primary care during disaster recovery. (Disaster Med Public Health Preparedness. 2016;10:492-495).

Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA.

Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters. We analyzed these networks to identify patterns of proximal student interactions in different classes and grades, to describe community structure within the schools, and to assess the impact of the physical environment of schools on proximal contacts. In the elementary and middle schools, we observed a high number of intra-grade and intra-classroom contacts and a relatively low number of inter-grade contacts. However, in high schools, contact networks were well connected and mixed across grades. High modularity of lower grades suggests that assumptions of homogeneous mixing in epidemic models may be inappropriate; whereas lower modularity in high schools suggests that homogenous mixing assumptions may be more acceptable in these settings. The results suggest that interventions targeting subsets of classrooms may work better in elementary schools than high schools. Our work presents quantitative measures of age-specific, school-based contacts that can be used as the basis for constructing models of the transmission of infections in schools.

An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services.

OBJECTIVE: Hurricane Sandy in the Rockaways, Queens, forced residents to evacuate and primary care providers to close or curtail operations. A large deficit in primary care access was apparent in the immediate aftermath of the storm. Our objective was to build a computational model to aid responders in planning to situate primary care services in a disaster-affected area. METHODS: Using an agent-based modeling platform, HAZEL, we simulated the Rockaways population, its evacuation behavior, and primary care providers' availability in the aftermath of Hurricane Sandy. Data sources for this model included post-storm and community health surveys from New York City, a survey of the Rockaways primary care providers, and research literature. The model then tested geospatially specific interventions to address storm-related access deficits. RESULTS: The model revealed that areas of high primary care access deficit were concentrated in the eastern part of the Rockaways. Placing mobile health clinics in the most populous census tracts reduced the access deficit significantly, whereas increasing providers' capacity by 50% reduced the deficit to a lesser degree. CONCLUSIONS: An agent-based model may be a useful tool to have in place so that policy makers can conduct scenario-based analyses to plan interventions optimally in the event of a disaster. (Disaster Med Public Health Preparedness. 2016;10:386-393).

State-level legal preparedness for nuclear and radiological emergencies in the U.S.: a network analysis of state laws and regulations.

OBJECTIVE: This study explored if and to what extent the laws of U.S. states mirrored the U.S. federal laws for responding to nuclear-radiological emergencies (NREs). METHODS: Emergency laws from a 12-state sample and the federal government were retrieved and translated into numeric codes representing acting agents, their partner agents, and the purposes of activity in terms of preparedness, response, and recovery. We used network analysis to explore the relationships among agents in terms of legally directed NRE activities. RESULTS: States' legal networks for NREs appear as not highly inclusive, involving an average of 28% of agents among those specified in the federal laws. Certain agents are highly central in NRE networks, so that their capacity and effectiveness might strongly influence an NRE response. CONCLUSIONS: State-level lawmakers and planners might consider whether or not greater inclusion of agents, modeled on the federal government laws, would enhance their NRE laws and if more agents should be engaged in planning and policy-making for NRE incidents. Further research should explore if and to what extent legislated NRE directives impose constraints on practical response activities including emergency planning.

Aflatoxin regulations and global pistachio trade: insights from social network analysis.

Aflatoxins, carcinogenic toxins produced by Aspergillus fungi, contaminate maize, peanuts, and tree nuts in many regions of the world. Pistachios are the main source of human dietary aflatoxins from tree nuts worldwide. Over 120 countries have regulations for maximum allowable aflatoxin levels in food commodities. We developed social network models to analyze the association between nations' aflatoxin regulations and global trade patterns of pistachios from 1996-2010. The main pistachio producing countries are Iran and the United States (US), which together contribute to nearly 75% of the total global pistachio market. Over this time period, during which many nations developed or changed their aflatoxin regulations in pistachios, global pistachio trade patterns changed; with the US increasingly exporting to countries with stricter aflatoxin standards. The US pistachio crop has had consistently lower levels of aflatoxin than the Iranian crop over this same time period. As similar trading patterns have also been documented in maize, public health may be affected if countries without aflatoxin regulations, or with more relaxed regulations, continually import crops with higher aflatoxin contamination. Unlike the previous studies on maize, this analysis includes a dynamic element, examining how trade patterns change over time with introduction or adjustment of aflatoxin regulations.