Planetary Protection Knowledge Gap Closure Enabling Crewed Missions to Mars.

As focus for exploration of Mars transitions from current robotic explorers to development of crewed missions, it remains important to protect the integrity of scientific investigations at Mars, as well as protect the Earth's biosphere from any potential harmful effects from returned martian material. This is the discipline of planetary protection, and the Committee on Space Research (COSPAR) maintains the consensus international policy and guidelines on how this is implemented. Based on National Aeronautics and Space Administration (NASA) and European Space Agency (ESA) studies that began in 2001, COSPAR adopted principles and guidelines for human missions to Mars in 2008. At that point, it was clear that to move from those qualitative provisions, a great deal of work and interaction with spacecraft designers would be necessary to generate meaningful quantitative recommendations that could embody the intent of the Outer Space Treaty (Article IX) in the design of such missions. Beginning in 2016, COSPAR then sponsored a multiyear interdisciplinary meeting series to address planetary protection "knowledge gaps" (KGs) with the intent of adapting and extending the current robotic mission-focused Planetary Protection Policy to support the design and implementation of crewed and hybrid exploration missions. This article describes the outcome of the interdisciplinary COSPAR meeting series, to describe and address these KGs, as well as identify potential paths to gap closure. It includes the background scientific basis for each topic area and knowledge updates since the meeting series ended. In particular, credible solutions for KG closure are described for the three topic areas of (1) microbial monitoring of spacecraft and crew health; (2) natural transport (and survival) of terrestrial microbial contamination at Mars, and (3) the technology and operation of spacecraft systems for contamination control. The article includes a KG data table on these topic areas, which is intended to be a point of departure for making future progress in developing an end-to-end planetary protection requirements implementation solution for a crewed mission to Mars. Overall, the workshop series has provided evidence of the feasibility of planetary protection implementation for a crewed Mars mission, given (1) the establishment of needed zoning, emission, transport, and survival parameters for terrestrial biological contamination and (2) the creation of an accepted risk-based compliance approach for adoption by spacefaring actors including national space agencies and commercial/nongovernment organizations.

Erratum: Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool. Diabetes Spectrum 2023;36:161-170 (https://doi.org/10.2337/ds22-0031).

[This corrects the article DOI: 10.2337/ds22-0031.].

Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool.

Objective: To assess whether an electronic health record (EHR)-based diabetes intensification tool can improve the rate of A1C goal attainment among patients with type 2 diabetes and an A1C ≥8%. Methods: An EHR-based tool was developed and sequentially implemented in a large, integrated health system using a four-phase, stepped-wedge design (single pilot site [phase 1] and then three practice site clusters [phases 2-4]; 3 months/phase), with full implementation during phase 4. A1C outcomes, tool usage, and treatment intensification metrics were compared retrospectively at implementation (IMP) sites versus nonimplementation (non-IMP) sites with sites matched on patient population characteristics using overlap propensity score weighting. Results: Overall, tool utilization was low among patient encounters at IMP sites (1,122 of 11,549 [9.7%]). During phases 1-3, the proportions of patients achieving the A1C goal (<8%) were not significantly improved between IMP and non-IMP sites at 6 months (range 42.9-46.5%) or 12 months (range 46.5-53.1%). In phase 3, fewer patients at IMP sites versus non-IMP sites achieved the goal at 12 months (46.7 vs. 52.3%, P = 0.02). In phases 1-3, mean changes in A1C from baseline to 6 and 12 months (range -0.88 to -1.08%) were not significantly different between IMP and non-IMP sites. Times to intensification were similar between IMP and non-IMP sites. Conclusion: Utilization of a diabetes intensification tool was low and did not influence rates of A1C goal attainment or time to treatment intensification. The low level of tool adoption is itself an important finding highlighting the problem of therapeutic inertia in clinical practice. Testing additional strategies to better incorporate, increase acceptance of, and improve proficiency with EHR-based intensification tools is warranted.

Unmet needs and opportunities for optimal management of patients with type 2 diabetes and chronic kidney disease.

This brief report utilizes EHR data from a large US health system to summarize unmet needs in patients with type 2 diabetes and chronic kidney disease and identifies areas of opportunity to optimize management within this patient population from treatment, screening and monitoring, and health care resource use perspectives.

Association between first-line monotherapy with metformin and the risk of atrial fibrillation (AMRAF) in patients with type 2 diabetes.

BACKGROUND: Type 2 diabetes (T2D) has a strong association with atrial fibrillation (AF) which increases risk of thromboembolic events, heart failure, and frequent hospitalizations. Metformin is the first-line medication for T2D with proposed anti-inflammatory, pro-metabolic, and cardio-protective benefits. Our objective was to investigate if initial therapy with metformin is associated with reduced incidence of AF in comparison to other non-insulin anti-hyperglycemic agents in patients with newly diagnosed T2D. METHODS: This retrospective cohort analysis included adults with a new diagnosis of T2D who were started on monotherapy (except insulin) between 2007 and 2017, without prior anti-hyperglycemic agent use, history of arrhythmias, or estimated GFR (eGFR) ≤ 30 ml/min. A multivariate analysis was performed using a fine-gray regression competing risk analysis to control for confounding variables after which pooled hazard ratios and 95 % confidence intervals were reported. Patients were followed until the end of study date, development of AF, addition of more anti-hyperglycemic agents, or death, whichever occurred first. RESULTS: Among 4584 metformin initiators compared to 1080 non-metformin monotherapy initiators, 10-year cumulative incidence of AF in metformin group was 5.2 % as compared to 8.1 % with other agents which was not statistically significant. Competing risk analysis did not demonstrate reduced rates of AF with metformin use (HR 0.92, 95 % CI 0.69 to 1.21; P = 0.55). Increased age and the presence of congestive heart failure were associated with significantly higher risk of AF in both groups (HR: 1.29, 95 % CI: 1.21 to 1.37; P ≤ 0.001; HR: 2.73, 95 % CI: 1.62 to 4.61; P ≤ 0.001, respectively). CONCLUSION: Initiation of metformin as a first line monotherapy for T2D, when compared to other non-insulin monotherapies, was not associated with decreased risk of developing AF in this retrospective observational study.

Vectorial capacities for malaria in eastern Amazonian Brazil depend on village, vector species, season, and parasite species.

BACKGROUND: The vector species in the Amazon River Basin are regionally and locally diverse, which makes it imperative to understand and compare their roles in malaria transmission to help select appropriate methods of intervention and evaluation. The major aim of this study was to measure the vectorial capacity of five Anopheles species in three neighbouring villages, for two Plasmodium parasite species affecting humans. METHODS: From 32 consecutive months of sampling in three villages, 1.5-7.0 km apart, on the Matapi River, Amapá State, Brazil, vectorial capacities (C) were estimated as time series for An. darlingi, An. marajoara, An. nuneztovari, An. triannulatus, and An. intermedius. Monthly parity measurements for each vector species were used to estimate daily survivorship and compared to estimates of survivorship from mark-release-recapture experiments. Gonotrophic cycle lengths were estimated through a time-series analysis of parity data, and durations of sporogony at study site temperatures for the two malaria parasite species were estimated from previous literature. RESULTS: The absolute abundances of five vector species were strongly tracked by the spatial variation in C among villages. Temporally, C varied between wet and dry seasons, with An. darlingi, An. marajoara and An. triannulatus exhibiting higher C in the dry season from August to December, and An. nuneztovari its highest C early in the rainy season in January and February. Anopheles intermedius exhibited higher C in the rainy season from April to June than in the dry season. Significant differences in overall survival for each independent variable, and a significant difference in C between wet and dry seasons, among villages, and among vector species for both Plasmodium falciparum and Plasmodium vivax. A generalized linear mixed model (GLMM) analysis by village showed significant effects of vector species on C in only one village, but significant effects of parasite species in all three. Although the GLMM analysis detected no significant parasite x vector species interaction effects on C, effects on C of spline regressions of C dynamics x vector species interactions were significant in all villages. CONCLUSIONS: These detailed analyses of entomological and parasitological variables revealed hidden complexities of malaria epidemiology at local scales in neighbouring riverine villages of the Amazon Region.

Perioperative management of diabetes in patients undergoing bariatric and metabolic surgery: a narrative review and the Cleveland Clinic practical recommendations.

Bariatric and metabolic surgery is an effective treatment for patients with severe obesity and obesity-related diseases. In patients with type 2 diabetes, it provides marked improvement in glycemic control and even remission of diabetes. In patients with type 1 diabetes, bariatric surgery may offer improvement in insulin sensitivity and other cardiometabolic risk factors, as well as amelioration of the mechanical complications of obesity. Because of these positive outcomes, there are increasing numbers of patients with diabetes who undergo bariatric surgical procedures each year. Prior to surgery, efforts should be made to optimize glycemic control. However, there is no need to delay or withhold bariatric surgery until a specific glycosylated hemoglobin target is reached. Instead, treatment should focus on avoidance of early postoperative hyperglycemia. In general, oral glucose-lowering medications and noninsulin injectables are not favored to control hyperglycemia in the inpatient setting. Hyperglycemia in the hospital is managed with insulin, aiming for perioperative blood glucose concentrations between 80 and 180 mg/dL. Following surgery, substantial changes of the antidiabetic medication regimens are common. Patients should have a clear understanding of the modifications made to their treatment and should be followed closely thereafter. In this review article, we describe practical recommendations for the perioperative management of diabetes in patients with type 2 or type 1 diabetes undergoing bariatric surgery. Specific recommendations are delineated based on the different treatments that are currently available for glycemic control, including oral glucose-lowering medications, noninsulin injectables, and a variety of insulin regimens.

Associations of weight loss with obesity-related comorbidities in a large integrated health system.

AIMS: To determine the health outcomes associated with weight loss in individuals with obesity, and to better understand the relationship between disease burden (disease burden; ie, prior comorbidities, healthcare utilization) and weight loss in individuals with obesity by analysing electronic health records (EHRs). MATERIALS AND METHODS: We conducted a case-control study using deidentified EHR-derived information from 204 921 patients seen at the Cleveland Clinic between 2000 and 2018. Patients were aged ≥20 years with body mass index ≥30 kg/m2 and had ≥7 weight measurements, over ≥3 years. Thirty outcomes were investigated, including chronic and acute diseases, as well as psychological and metabolic disorders. Weight change was investigated 3, 5 and 10 years prior to an event. RESULTS: Weight loss was associated with reduced incidence of many outcomes (eg, type 2 diabetes, nonalcoholic steatohepatitis/nonalcoholic fatty liver disease, obstructive sleep apnoea, hypertension; P < 0.05). Weight loss >10% was associated with increased incidence of certain outcomes including stroke and substance abuse. However, many outcomes that increased with weight loss were attenuated by disease burden adjustments. CONCLUSIONS: This study provides the most comprehensive real-world evaluation of the health impacts of weight change to date. After comorbidity burden and healthcare utilization adjustments, weight loss was associated with an overall reduction in risk of many adverse outcomes.

A Type 2 Diabetes Subtype Responsive to ACCORD Intensive Glycemia Treatment.

OBJECTIVE: Current type 2 diabetes (T2D) management contraindicates intensive glycemia treatment in patients with high cardiovascular disease (CVD) risk and is partially motivated by evidence of harms in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Heterogeneity in response to intensive glycemia treatment has been observed, suggesting potential benefit for some individuals. RESEARCH DESIGN AND METHODS: ACCORD was a randomized controlled trial that investigated whether intensively treating glycemia in individuals with T2D would reduce CVD outcomes. Using a novel approach to cluster HbA1c trajectories, we identified groups in the intensive glycemia arm with modified CVD risk. Genome-wide analysis and polygenic score (PS) were developed to predict group membership. Mendelian randomization was performed to infer causality. RESULTS: We identified four clinical groupings in the intensive glycemia arm, and clinical group 4 (C4) displayed fewer CVD (hazard ratio [HR] 0.34; P = 2.01 × 10-3) and microvascular outcomes (HR 0.86; P = 0.015) than those receiving standard treatment. A single-nucleotide polymorphism, rs220721, in MAS1 reached suggestive significance in C4 (P = 4.34 × 10-7). PS predicted C4 with high accuracy (area under the receiver operating characteristic curve 0.98), and this predicted C4 displayed reduced CVD risk with intensive versus standard glycemia treatment (HR 0.53; P = 4.02 × 10-6), but not reduced risk of microvascular outcomes (P < 0.05). Mendelian randomization indicated causality between PS, on-trial HbA1c, and reduction in CVD outcomes (P < 0.05). CONCLUSIONS: We found evidence of a T2D clinical group in ACCORD that benefited from intensive glycemia treatment, and membership in this group could be predicted using genetic variants. This study generates new hypotheses with implications for precision medicine in T2D and represents an important development in this landmark clinical trial warranting further investigation.

The Probability of A1C Goal Attainment in Patients With Uncontrolled Type 2 Diabetes in a Large Integrated Delivery System: A Prediction Model.

OBJECTIVE: To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of hemoglobin A1c (A1C) goal attainment. RESEARCH DESIGN AND METHODS: This was a retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C >9%) were identified on the index date of 31 December 2016 (n = 6,973) and grouped by attainment (n = 1,653 [23.7%]) or nonattainment (n = 5,320 [76.3%]) of A1C <8% by 31 December 2017, and subgroups were compared on a number of demographic and clinical variables. On the basis of these variables, a nomogram was created for predicting probability of A1C goal attainment. RESULTS: For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%), and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common antidiabetes medications. Only 1,653 (23.7%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, dipeptidyl peptidase 4 inhibitor use, thiazolidinedione use, metformin use, glucagon-like peptide 1 receptor agonist use, and fewer classes of antidiabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). CONCLUSIONS: A minority of patients with an A1C >9% achieved an A1C <8% at 1 year. While most identified predictive factors are nonmodifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help to improve A1C goal attainment.

Noninsulin Diabetes Therapies in Older Adults.

Diabetes risk increases with age due to changes in ß-cell function and increased insulin resistance and is one of the most common chronic medical conditions in the elderly. Diabetes management in this population requires a multidisciplinary, patient-centric approach due to wide heterogeneity in patients' health and functional capacities. Meticulous assessment of each patient before formulating a regimen and thorough patient education are keys to success in achieving glycemic goals, which should be individualized. Lifestyle modification is recommended for every patient.

Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). RESEARCH DESIGN AND METHODS: From 2005 to 2017, we identified NSH events by diagnosis codes and NLP. We then built an SH prediction model. RESULTS: There were 204,517 patients with type 2 diabetes and no diagnosis codes for NSH. Evidence of NSH was found in 7,035 (3.4%) of patients using NLP. We reviewed 1,200 of the NLP-detected NSH notes and confirmed 93% to have NSH. The SH prediction model (C-statistic 0.806) showed increased risk with NSH (hazard ratio 4.44; P < 0.001). However, the model with NLP did not improve SH prediction compared with diagnosis code-only NSH. CONCLUSIONS: Detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction.

Association of Utilization Management Policy With Uptake of Hypofractionated Radiotherapy Among Patients With Early-Stage Breast Cancer.

Importance: Breast cancer accounts for the largest portion of cancer-related spending in the United States. Although hypofractionated radiotherapy after breast-conserving surgery is a cost-effective and convenient treatment strategy for patients with early-stage breast cancer, less than 40% of eligible women received hypofractionated radiotherapy in 2013. Objective: To assess the association of a large commercial payer's utilization management policy with the use of hypofractionated radiotherapy among women with early-stage breast cancer and its associated cost. Design, Setting, and Participants: A retrospective, adjusted difference-in-differences economic analysis was conducted using administrative claims data from January 1, 2012, to June 1, 2018, of women 18 years or older with early-stage breast cancer who were eligible for hypofractionated radiotherapy according to 2011 guidelines from the American Society for Radiation Oncology and were continuously enrolled in 14 geographically diverse commercial health plans covering 6.9% of US adult women. Women who received mastectomy, brachytherapy, or less than 11 or more than 40 external beam fractions of radiotherapy were excluded. A utilization management policy was used to encourage the use of hypofractionated radiotherapy among women in fully insured and Medicare Advantage (fully insured) plans. Under the new policy, claims for extended-course radiotherapy were not reimbursed for fully insured women who were eligible for hypofractionated radiotherapy. This policy did not apply to women in self-insured or Medicare supplemental insurance (self-insured) plans, allowing these groups to serve as a comparison group. Main Outcomes and Measures: The primary outcome was use of hypofractionated radiotherapy, and the secondary outcome was the cost of this type of radiotherapy. Results: Of 10 540 eligible women, 3619 (34.3%) were in fully insured plans and thus subject to the policy. There were no meaningful differences between the fully insured and self-insured groups in mean (SD) age at the start of radiotherapy (63.8 [8.6] vs 65.0 [8.9] years), mean (SD) Charlson Comorbidity Index score (3.0 [1.5] vs 3.2 [1.6]), or practice setting (outpatient hospital setting, 2982 of 3619 [82.4%] vs 5600 of 6921 [80.9%]). The policy was associated with an increase in use of hypofractionated radiotherapy among fully insured patients subject to the policy (adjusted percentage point difference-in-difference, 4.2%; 95% CI, 0.0%-8.4%; P = .05) and a nonsignificant decrease in radiotherapy-associated expenditures (-$2275 relative to self-insured patients; P = .09). Spillover analyses revealed a significantly higher uptake of hypofractionated radiotherapy among self-insured patients who were indirectly exposed to the policy (adjusted percentage point difference-in-difference, 8.5%; 95% CI, 3.6%-13.5%; P < .001) compared with those who were not exposed. Conclusions and Relevance: This study suggests that a payer's utilization management policy was associated with direct and spillover increases in the use of hypofractionated radiotherapy, even after accounting for a long-term secular trend in the uptake of hypofractionated radiotherapy in the control groups. Utilization management may promote evidence-based cancer care.

Risk prediction for severe hypoglycemia in a type 2 diabetes population with previous non-severe hypoglycemia.

BACKGROUND/AIM: Episodes of non-severe hypoglycemia can be captured through diagnoses documented in the electronic medical record. We aimed to create a clinically useful prediction model for a severe hypoglycemia event, requiring an emergency department visit or hospitalization, in patients with Type 2 diabetes with a history of non-severe hypoglycemia. METHODS: Using electronic medical record data from 50,439 patients with Type 2 diabetes in one health system, number of severe hypoglycemia events and associated patient characteristics from 2006 to 2015 were previously defined. Using the landmarking method, a dynamic prediction model was built using the subset of 1876 patients who had a documented non-severe hypoglycemia diagnosis code, using logistic regression to obtain landmark-specific odds of severe hypoglycemia in this group. For model performance, the bootstrap procedure was employed for internal validation and area under the curve (AUC) and index of prediction accuracy (IPA) were calculated. RESULTS: Glycosylated hemoglobin (HbA1c) less than 7% (53 mmol/mol) was associated with increased odds ratio (OR) of severe hypoglycemia at 3 months (OR 1.92 95% Confidence Interval (CI) 1.19-3.10 at HbA1c 5% (31 mmol/mol) and OR 1.21, CI 1.03-1.41 at HbA1c 6%(42 mmol/mol).) History of non-severe hypoglycemia within the past 3 months increased odds for severe hypoglycemia (OR 2.58 95% CI 1.80-3.70) as did Black race, insulin use with the past 3 months, and comorbidities. Metformin and sulfonlylurea use in the past 3 months, increasing age and body mass index had lower odds of a future severe hypoglycemia event. For the prediction model for 3 month risk of severe hypoglycemia, the AUC was 0.890 (CI 0.843-0.907) and the IPA was 10.8% (CI 4.4% - 12.4%). CONCLUSION: In patients with a documented diagnosis of non-severe hypoglycemia, a dynamic prediction model identifies patients with Type 2 diabetes with 3-month increased risk of severe hypoglycemia, allowing for preventive efforts, such as medication changes, at the point of care.

Increased sensitivity to traumatic axonal injury on postconcussion diffusion tensor imaging scans in National Football League players by using premorbid baseline scans.

OBJECTIVE: Statistical challenges exist when using diffusion tensor imaging (DTI) to assess traumatic axonal injury (TAI) in individual concussed athletes. The authors examined active professional American football players over a 6-year time period to study potential TAI after concussion and assess optimal methods to analyze DTI at the individual level. METHODS: Active American professional football players recruited prospectively were assessed with DTI, conventional MRI, and standard clinical workup. Subjects underwent an optional preseason baseline scan and were asked to undergo a scan within 5 days of concussion during gameplay. DTI from 25 age- and sex-matched controls were obtained. Both semiautomated region-of-interest analysis and fully automated tract-based spatial statistics (TBSS) were used to examine DTI at individual and group levels. Statistical differences were assessed comparing individual DTI data to baseline imaging versus a normative database. Group-level comparisons were also performed to determine if longer exposure to professional-level play or prior concussion cause white matter microstructural integrity changes. RESULTS: Forty-nine active professional football players were recruited into the study. Of the 49 players, 7 were assessed at baseline during the preseason and after acute concussion. An additional 18 players were assessed after acute concussion only. An additional 24 players had only preseason baseline assessments. The results suggest DTI is more sensitive to suspected TAI than conventional MRI, given that 4 players demonstrated decreased fractional anisotropy (FA) in multiple tracts despite normal conventional MRI. Furthermore, the data suggest individual assessment of DTI data using baseline premorbid imaging is more sensitive than typical methods of comparing data to a normative control group. Among all subjects with baseline data, 1 reduced FA tract (± 2.5 standard deviations) was found using the typical normative database reference versus 10 statistically significant (p < 0.05) reduced FA tracts when referencing internal control baseline data. All group-level comparisons were statistically insignificant (p > 0.05). CONCLUSIONS: Baseline premorbid DTI data for individual DTI analysis provides increased statistical sensitivity. Specificity using baseline imaging also increases because numerous potential etiologies for reduced FA may exist prior to a concussion. These data suggest that there is a high potential for false-positive and false-negative assessment of DTI data using typical methods of comparing an individual to normative groups given the variability of FA values in the normal population.

The ecology of mosquito larvae (Diptera: Culicidae) in the subalpine zone of the eastern Sierra Nevada Mountains, California, U.S.A.

Mosquito larvae were collected from the subalpine region of the eastern Sierra Nevada Mountains from 2011 to 2014. Two watersheds were sampled and sites selected were mainly vernal snow-melt pools and wet meadows. Seven Aedes species, Culiseta incidens (Thomson), and Culex tarsalis Coquillett were collected. The most abundant and widely distributed species were Ae. hexodontus Dyar and Ae. tahoensis Dyar. Aedes tahoensis was the predominate species in woodland snow-melt habitats. Some species were found at most elevations while others were found more often at specific elevations. The most restrictive species was Ae. ventrovittis Dyar which occurred almost exclusively between 3,219 m a.s.l. and 3,390 m a.s.l. Shannon and Simpson species diversity indices demonstrated that species diversity was greater in meadow habitats compared to woodland habitats. Mixed woodland/meadows, rock pools, and shallow grass pools were intermediate in species diversity. Abiotic factors such as snowpack and water temperature impacted species development times and when habitats dried. It was concluded that spatial and temporal patterns of habitats, along with elevation, influenced species presence and larval development. The results of the present study and previous work in the eastern Sierras will help guide future research that focuses on the potential change in the distribution and seasonality of subalpine mosquitoes and disease potential in the eastern Sierras as climatic conditions change.