Association of Mental Health Conditions, Recent Stressful Life Events, and Adverse Childhood Experiences with Postpartum Substance Use - Seven States, 2019-2020.

Most pregnancy-related deaths due to mental health conditions, which include overdose and poisoning related to substance use disorder, occur during the late (43-365-day) postpartum period (1). Adverse childhood experiences and stressful life events are associated with increased substance use during pregnancy (2,3). Pregnancy Risk Assessment Monitoring System (PRAMS) respondents in seven states with high opioid overdose mortality rates were recontacted 9-10 months after giving birth in 2019 and asked about postpartum prescription opioid misuse,* tobacco use, unhealthy alcohol use,† and use of other substances.§ Substance and polysubstance use prevalence estimates were calculated, stratified by mental health and social adversity indicators. Overall, 25.6% of respondents reported postpartum substance use, and 5.9% reported polysubstance use. The following conditions were associated with higher substance and polysubstance use prevalence in postpartum women: depressive symptoms, depression, anxiety, adverse childhood experiences, and stressful life events. Substance use prevalence was higher among women who experienced six or more stressful life events during the year preceding the birth (67.1%) or four adverse childhood experiences related to household dysfunction (57.9%). One in five respondents who experienced six or more stressful life events in the year before giving birth and 26.3% of women with four adverse childhood experiences reported postpartum polysubstance use. Clinical and community- and systems-level interventions to improve postpartum health can include screening and treatment for depression, anxiety, and substance use disorders during the postpartum period. Evidence-based strategies can prevent adverse childhood experiences and mitigate the immediate and long-term harms.¶.

Vital Signs: Maternity Care Experiences - United States, April 2023.

Introduction: Maternal deaths increased in the United States during 2018-2021, with documented racial disparities. Respectful maternity care is a component of quality care that includes preventing harm and mistreatment, engaging in effective communication, and providing care equitably. Improving respectful maternity care can be part of multilevel strategies to reduce pregnancy-related deaths. Methods: CDC analyzed data from the PN View Moms survey administered during April 24-30, 2023, to examine the following components of respectful care: 1) experiences of mistreatment (e.g., violations of physical privacy, ignoring requests for help, or verbal abuse), 2) discrimination (e.g., because of race, ethnicity or skin color; age; or weight), and 3) reasons for holding back from communicating questions or concerns during maternity (pregnancy or delivery) care. Results: Among U.S. mothers with children aged <18 years, 20% reported mistreatment while receiving maternity care for their youngest child. Approximately 30% of Black, Hispanic, and multiracial respondents and approximately 30% of respondents with public insurance or no insurance reported mistreatment. Discrimination during the delivery of maternity care was reported by 29% of respondents. Approximately 40% of Black, Hispanic, and multiracial respondents reported discrimination, and approximately 45% percent of all respondents reported holding back from asking questions or discussing concerns with their provider. Conclusions and implications for public health practice: Approximately one in five women reported mistreatment during maternity care. Implementing quality improvement initiatives and provider training to encourage a culture of respectful maternity care, encouraging patients to ask questions and share concerns, and working with communities are strategies to improve respectful maternity care.

Lessons Learned from Programmatic Gains in HIV Service Delivery During the COVID-19 Pandemic - 41 PEPFAR-Supported Countries, 2020.

The U.S. President's Emergency Plan for AIDS Relief (PEPFAR) supports country programs in identifying persons living with HIV infection (PLHIV), providing life-saving treatment, and reducing the spread of HIV in countries around the world (1,2). CDC used Monitoring, Evaluation, and Reporting (MER) data* to assess the extent to which COVID-19 mitigation strategies affected HIV service delivery across the HIV care continuum† globally during the first year of the COVID-19 pandemic. Indicators included the number of reported HIV-positive test results, the number of PLHIV who were receiving antiretroviral therapy (ART), and the rates of HIV viral load suppression. Percent change in performance was assessed between countries during the first 3 months of 2020, before COVID-19 mitigation efforts began (January-March 2020), and the last 3 months of the calendar year (October-December 2020). Data were reviewed for all 41 countries to assess total and country-level percent change for each indicator. Then, qualitative data were reviewed among countries in the upper quartile to assess specific strategies that contributed to programmatic gains. Overall, positive percent change was observed in PEPFAR-supported countries in HIV treatment (5%) and viral load suppression (2%) during 2020. Countries reporting the highest gains across the HIV care continuum during 2020 attributed successes to reducing or streamlining facility attendance through strategies such as enhancing index testing (offering of testing to the biologic children and partners of PLHIV)§ and community- and home-based testing; treatment delivery approaches; and improvements in data use through monitoring activities, systems, and data quality checks. Countries that reported program improvements during the first year of the COVID-19 pandemic offer important information about how lifesaving HIV treatment might be provided during a global public health crisis.

OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing.

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.

Coronavirus Disease 2019 (COVID-19) in Americans Aboard the Diamond Princess Cruise Ship.

BACKGROUND: The Diamond Princess cruise ship was the site of a large outbreak of coronavirus disease 2019 (COVID-19). Of 437 Americans and their travel companions on the ship, 114 (26%) tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We interviewed 229 American passengers and crew after disembarkation following a ship-based quarantine to identify risk factors for infection and characterize transmission onboard the ship. RESULTS: The attack rate for passengers in single-person cabins or without infected cabinmates was 18% (58/329), compared with 63% (27/43) for those sharing a cabin with an asymptomatic infected cabinmate, and 81% (25/31) for those with a symptomatic infected cabinmate. Whole genome sequences from specimens from passengers who shared cabins clustered together. Of 66 SARS-CoV-2-positive American travelers with complete symptom information, 14 (21%) were asymptomatic while on the ship. Among SARS-CoV-2-positive Americans, 10 (9%) required intensive care, of whom 7 were ≥70 years. CONCLUSIONS: Our findings highlight the high risk of SARS-CoV-2 transmission on cruise ships. High rates of SARS-CoV-2 positivity in cabinmates of individuals with asymptomatic infections suggest that triage by symptom status in shared quarters is insufficient to halt transmission. A high rate of intensive care unit admission among older individuals complicates the prospect of future cruise travel during the pandemic, given typical cruise passenger demographics. The magnitude and severe outcomes of this outbreak were major factors contributing to the Centers for Disease Control and Prevention's decision to halt cruise ship travel in US waters in March 2020.

Use of US Public Health Travel Restrictions during COVID-19 Outbreak on Diamond Princess Ship, Japan, February-April 2020.

Public health travel restrictions (PHTR) are crucial measures during communicable disease outbreaks to prevent transmission during commercial airline travel and mitigate cross-border importation and spread. We evaluated PHTR implementation for US citizens on the Diamond Princess during its coronavirus disease (COVID-19) outbreak in Japan in February 2020 to explore how PHTR reduced importation of COVID-19 to the United States during the early phase of disease containment. Using PHTR required substantial collaboration among the US Centers for Disease Control and Prevention, other US government agencies, the cruise line, and public health authorities in Japan. Original US PHTR removal criteria were modified to reflect international testing protocols and enable removal of PHTR for persons who recovered from illness. The impact of PHTR on epidemic trajectory depends on the risk for transmission during travel and geographic spread of disease. Lessons learned from the Diamond Princess outbreak provide critical information for future PHTR use.

Patterns in COVID-19 Vaccination Coverage, by Social Vulnerability and Urbanicity - United States, December 14, 2020-May 1, 2021.

Disparities in vaccination coverage by social vulnerability, defined as social and structural factors associated with adverse health outcomes, were noted during the first 2.5 months of the U.S. COVID-19 vaccination campaign, which began during mid-December 2020 (1). As vaccine eligibility and availability continue to expand, assuring equitable coverage for disproportionately affected communities remains a priority. CDC examined COVID-19 vaccine administration and 2018 CDC social vulnerability index (SVI) data to ascertain whether inequities in COVID-19 vaccination coverage with respect to county-level SVI have persisted, overall and by urbanicity. Vaccination coverage was defined as the number of persons aged ≥18 years (adults) who had received ≥1 dose of any Food and Drug Administration (FDA)-authorized COVID-19 vaccine divided by the total adult population in a specified SVI category.† SVI was examined overall and by its four themes (socioeconomic status, household composition and disability, racial/ethnic minority status and language, and housing type and transportation). Counties were categorized into SVI quartiles, in which quartile 1 (Q1) represented the lowest level of vulnerability and quartile 4 (Q4), the highest. Trends in vaccination coverage were assessed by SVI quartile and urbanicity, which was categorized as large central metropolitan, large fringe metropolitan (areas surrounding large cities, e.g., suburban), medium and small metropolitan, and nonmetropolitan counties.§ During December 14, 2020-May 1, 2021, disparities in vaccination coverage by SVI increased, especially in large fringe metropolitan (e.g., suburban) and nonmetropolitan counties. By May 1, 2021, vaccination coverage was lower among adults living in counties with the highest overall SVI; differences were most pronounced in large fringe metropolitan (Q4 coverage = 45.0% versus Q1 coverage = 61.7%) and nonmetropolitan (Q4 = 40.6% versus Q1 = 52.9%) counties. Vaccination coverage disparities were largest for two SVI themes: socioeconomic status (Q4 = 44.3% versus Q1 = 61.0%) and household composition and disability (Q4 = 42.0% versus Q1 = 60.1%). Outreach efforts, including expanding public health messaging tailored to local populations and increasing vaccination access, could help increase vaccination coverage in high-SVI counties.

Public Health Responses to COVID-19 Outbreaks on Cruise Ships - Worldwide, February-March 2020.

An estimated 30 million passengers are transported on 272 cruise ships worldwide each year* (1). Cruise ships bring diverse populations into proximity for many days, facilitating transmission of respiratory illness (2). SARS-CoV-2, the virus that causes coronavirus disease (COVID-19) was first identified in Wuhan, China, in December 2019 and has since spread worldwide to at least 187 countries and territories. Widespread COVID-19 transmission on cruise ships has been reported as well (3). Passengers on certain cruise ship voyages might be aged ≥65 years, which places them at greater risk for severe consequences of SARS-CoV-2 infection (4). During February-March 2020, COVID-19 outbreaks associated with three cruise ship voyages have caused more than 800 laboratory-confirmed cases among passengers and crew, including 10 deaths. Transmission occurred across multiple voyages of several ships. This report describes public health responses to COVID-19 outbreaks on these ships. COVID-19 on cruise ships poses a risk for rapid spread of disease, causing outbreaks in a vulnerable population, and aggressive efforts are required to contain spread. All persons should defer all cruise travel worldwide during the COVID-19 pandemic.

Social Role-Related Stress and Social Role-Related Reward as Related to Subsequent Subclinical Cardiovascular Disease in a Longitudinal Study of Midlife Women: The Study of Women's Health Across the Nation.

OBJECTIVE: The purpose of this study was to determine if midlife social role quality, defined by the stress and rewards associated with four social roles, is related to later-life subclinical cardiovascular disease (SCVD) in a cohort of women transitioning through menopause. METHODS: The Study of Women's Health Across the Nation (SWAN) is a longitudinal cohort study of midlife women. Stress and reward from four social roles (spouse, parent, employee, caregiver) were assessed at seven early visits. Later-life SCVD was assessed via carotid ultrasound and brachial-ankle pulse wave velocity at two later visits. We tested whether ever reporting an "extremely" or "quite a bit" stressful role was related to SCVD. We also tested whether cumulative stress and reward, as well as baseline and change in stress and reward were related to SCVD, adjusting for demographics and cardiovascular risk factors. RESULTS: Among 1602 women, reporting a stressful role during midlife (between ages 47 and 52 years) was associated with later-life (age 61 years) carotid intima-media thickness, which was 21 µm thicker than never reporting a stressful role. No significant relationships between stressful roles and other SCVD measures were identified. Cumulative and baseline change models of stress and reward were not related to SCVD. CONCLUSION: A stressful social role in midlife was associated with greater atherosclerotic burden in later-life in a cohort of women transitioning through menopause. Social role rewards were unrelated to better later-life SCVD. These findings extend the knowledge of stress and cardiovascular disease in women by using measures of stress and reward for multiple social roles over the years of midlife.

Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets.

BACKGROUND: There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. METHODS: We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. RESULTS: We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. CONCLUSIONS: As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

Physical activity trajectories during midlife and subsequent risk of physical functioning decline in late mid-life: The Study of Women's Health Across the Nation (SWAN).

The purpose of this study was to examine the importance of midlife physical activity on physical functioning in later life. Data are from 1771 Study of Women's Health Across the Nation (SWAN) participants, aged 42-52 (46.4±2.7) years at baseline (1996-97). Latent class growth analysis was used to identify physical activity trajectory groups using reported sports and exercise index data collected at seven time-points from baseline to Visit 13 (2011-13); objective measures of physical functioning performance were collected at Visit 13. The sports and exercise index (henceforth: physical activity) is a measure of moderate to vigorous intensity physical activity during discretionary periods of the day. Multivariable linear regression analyses were used to model each continuous physical performance measure as a function of the physical activity trajectory class. Across midlife, five physical activity trajectory classes emerged, including: lowest (26.2% of participants), increasing (13.4%), decreasing (22.4%), middle (23.9%), and highest (14.1%) physical activity. After full adjustment, women included in the middle and highest physical activity groups demonstrated ≥5% better physical functioning performance than those who maintained low physical activity levels (all comparisons; p<0.05). Statistically significant differences were also noted when physical activity trajectory groups were compared to the increasing physical activity group. Results from the current study support health promotion efforts targeting increased (or maintenance of) habitual physical activity in women during midlife to reduce future risk of functional limitations and disability. These findings have important public health and clinical relevance as future generations continue to transition into older adulthood.

What is the optimal recall period for verbal autopsies? Validation study based on repeat interviews in three populations.

BACKGROUND: One key contextual feature in Verbal Autopsy (VA) is the time between death and survey administration, or recall period. This study quantified the effect of recall period on VA performance by using a paired dataset in which two VAs were administered for a single decedent. METHODS: This study used information from the Population Health Metrics Research Consortium (PHMRC) Study, which collected VAs for "gold standard" cases where cause of death (COD) was supported by clinical criteria. This study repeated VA interviews within 3-52 months of death in PHMRC study sites in Andhra Pradesh, India, and Bohol and Manila, Philippines. The final dataset included 2113 deaths interviewed twice and with recall periods ranging from 0 to 52 months. COD was assigned by the Tariff method and its accuracy determined by comparison with the gold standard COD. RESULTS: The probability of a correct diagnosis of COD decreased by 0.55 % per month in the period after death. Site of data collection and survey module also affected the probability of Tariff Method correctly assigning a COD. The probability of a correct diagnosis in VAs collected 3-11 months after death will, on average, be 95.9 % of that in VAs collected within 3 months of death. CONCLUSIONS: These findings suggest that collecting VAs within 3 months of death may improve the quality of the information collected, taking the need for a period of mourning into account. This study substantiates the WHO recommendation that it is reasonable to collect VAs up to 1 year after death providing it is accepted that probability of a correct diagnosis is likely to decline month by month during this period.

The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy.

BACKGROUND: We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. METHODS: The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. RESULTS: A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low (kappa = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument (kappa = 0.497) and when analyzed at the level of the individual decedent (kappa = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. CONCLUSIONS: Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent subsets of symptoms to enable the Tariff Method to assign a COD. Questions which contributed most to COD prediction were also the most reliable and consistent across repeat interviews; these have been included in the short form VA questionnaire. Accuracy and reliability of diagnosis for an individual death depend on the quality of interview. This has considerable implications for the progressive roll out of VAs into civil registration and vital statistics (CRVS) systems.

Validating estimates of prevalence of non-communicable diseases based on household surveys: the symptomatic diagnosis study.

BACKGROUND: Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms ("Symptomatic Diagnosis," or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas. METHODS: As part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels. RESULTS: The questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6-66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818-0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods. CONCLUSIONS: SD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.

A shortened verbal autopsy instrument for use in routine mortality surveillance systems.

BACKGROUND: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. METHODS: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. RESULTS: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55%. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4%, 0.0%, and 0.6% for the adult, child, and neonatal modules, respectively. CONCLUSIONS: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50% without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

Improving performance of the Tariff Method for assigning causes of death to verbal autopsies.

BACKGROUND: Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method. METHODS: This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database. RESULTS: For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5%, 7.4%, and 14.9% for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0%, 13.5%, and 21.2%, respectively. Similar levels of improvement are seen in analyses without HCE. CONCLUSIONS: Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods.

BACKGROUND: Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. METHODS: We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. RESULTS: Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. CONCLUSIONS: Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Long-acting reversible contraception use and unmet desire among patients after the Zika Contraception Access Network Program in Puerto Rico.

OBJECTIVES: To describe unmet desire for long-acting reversible contraception (LARC) after the Zika Contraception Access Network (Z-CAN) in Puerto Rico during the 2016-2017 Zika outbreak. STUDY DESIGN: Z-CAN patients completed surveys about contraception experiences over a 3-year period. RESULTS: Of 1809 respondents, 3% never used LARC but reported wanting it since their initial visit. As reasons for not getting LARC, nearly 50% indicated a provider-related reason and 25% reported cost. CONCLUSIONS: Few Z-CAN patients who never used LARC had unmet desire. Provider training in contraception guidelines and strategies to address costs can expand access to the full range of reversible contraception. IMPLICATIONS: Three years after a short-term program provided reversible contraception in Puerto Rico, few respondents had never used but wanted a long-acting reversible contraception method. Nearly half reported provider-related reasons for not receiving long-acting reversible contraception, and 25% reported cost. Provider awareness of contraceptive guidance and method availability can support client-centered care.

Katanin p60-like1 promotes microtubule growth and terminal dendrite stability in the larval class IV sensory neurons of Drosophila.

Dendrite shape is considered a defining component of neuronal function. Yet, the mechanisms specifying diverse dendritic morphologies, and the extent to which their function depends on these morphologies, remain unclear. Here, we demonstrate a requirement for the microtubule-severing protein katanin p60-like 1 (Kat-60L1) in regulating the elaborate dendrite morphology and nocifensive functions of Drosophila larval class IV dendritic arborization neurons. Kat-60L1 mutants exhibit diminished responsiveness to noxious mechanical and thermal stimuli. Class IV dendrite branch number and length are also reduced, supporting a correspondence between neuronal function and the full extent of the dendritic arbor. These arborization defects occur particularly in late larval development, and live imaging reveals that Kat-60L1 is required for dynamic, filopodia-like nascent branches to stabilize during this stage. Mutant dendrites exhibit fewer EB1-GFP-labeled microtubules, suggesting that Kat-60L1 increases polymerizing microtubules to establish terminal branch stability and full arbor complexity. Although loss of the related microtubule-severing protein Spastin also reduces the class IV dendrite arbor, microtubule polymerization within dendrites is unaffected. Conversely, Spastin overexpression destroys stable microtubules within these neurons, while Kat-60L1 has no effect. Kat-60L1 thus sculpts the class IV dendritic arbor through microtubule regulatory mechanisms distinct from Spastin. Our data support differential roles of microtubule-severing proteins in regulating neuronal morphology and function, and provide evidence that dendritic arbor development is the product of multiple pathways functioning at distinct developmental stages.