Thelazia callipaeda Eyeworms in American Black Bear, Pennsylvania, USA, 2023.

We identified a Thelazia callipaeda eyeworm in an American black bear in Pennsylvania, USA, on the basis of its morphological features and molecular analysis. Our finding highlights emergence of a T. callipaeda worm sylvatic transmission cycle in the United States.

Pregnant women's perceptions on Information Sources on Zika Virus: a qualitative study.

The Zika virus (ZIKV) epidemic had a sanitary, psychosocial, and economic impact on individuals of reproductive age. The primary concern revolved around infection during pregnancy due to possible vertical transmission and its association with adverse fetal and infant outcomes, known as Congenital Zika Syndrome (CZS). This qualitative study employs phenomenology and grounded theory. This study includes interviews with 98 women, some pregnant during the ZIKV epidemic in Brazil, Colombia, and Puerto Rico, who had children with CZS or without diagnosed neurological impairment. Additionally, the study included a group of women who were pregnant during the COVID-19 pandemic in these same countries. In both groups, interviewees had varying levels of knowledge about ZIKV. The study found that messages conveyed through the media tended to be alarmist, in contrast to the information provided by healthcare professionals, which was considered more trustworthy. Pregnant women during the ZIKV epidemic reported receiving their ZIKV and CSZ infection diagnoses late, either during or after childbirth. The study underscores the needs of pregnant women in high-risk scenarios, the importance of health education processes, and the necessity to reinforce communication and continuing education.

A epidemia do vírus Zika (ZIKV) teve impacto sanitário, psicossocial e econômico sobre pessoas em idade reprodutiva. A principal preocupação foi a infecção durante a gravidez devido a possível transmissão vertical e sua associação com resultados fetais e infantis adversos, conhecida como síndrome congênita associada à infecção pelo Vírus Zika (SCZ). Este estudo qualitativo utiliza a fenomenologia e a teoria fundamentada. O estudo inclui entrevistas com 98 mulheres, parte grávida durante a epidemia de ZIKV no Brasil, Colômbia e Porto Rico e que tiveram filhos com SCZ ou sem comprometimento neurológico diagnosticado. Além disso, o estudo inclui um grupo de mulheres grávidas durante a pandemia de COVID-19 nos mesmos países. Em ambos os grupos, as entrevistadas tinham diferentes níveis de conhecimento sobre ZIKV. O estudo constatou que as mensagens veiculadas por meio da mídia eram alarmistas; em contraste com as informações fornecidas por profissionais de saúde, consideradas mais confiáveis. Mulheres gestantes durante a epidemia do ZIKV relataram ter recebido seu diagnóstico de infecção por ZIKV e SCZ tardiamente ou após o parto. O estudo destaca as necessidades das mulheres grávidas em cenários de alto risco, a importância de processos de educação em saúde e a necessidade de reforçar a comunicação e a educação continuada.

Correction: Pooled Cohort Profile: ReCoDID Consortium's Harmonized Acute Febrile Illness Arbovirus Meta-Cohort.

[This corrects the article DOI: 10.2196/54281.].

Pooled Cohort Profile: ReCoDID Consortium's Harmonized Acute Febrile Illness Arbovirus Meta-Cohort.

Infectious disease (ID) cohorts are key to advancing public health surveillance, public policies, and pandemic responses. Unfortunately, ID cohorts often lack funding to store and share clinical-epidemiological (CE) data and high-dimensional laboratory (HDL) data long term, which is evident when the link between these data elements is not kept up to date. This becomes particularly apparent when smaller cohorts fail to successfully address the initial scientific objectives due to limited case numbers, which also limits the potential to pool these studies to monitor long-term cross-disease interactions within and across populations. CE data from 9 arbovirus (arthropod-borne viruses) cohorts in Latin America were retrospectively harmonized using the Maelstrom Research methodology and standardized to Clinical Data Interchange Standards Consortium (CDISC). We created a harmonized and standardized meta-cohort that contains CE and HDL data from 9 arbovirus studies from Latin America. To facilitate advancements in cross-population inference and reuse of cohort data, the Reconciliation of Cohort Data for Infectious Diseases (ReCoDID) Consortium harmonized and standardized CE and HDL from 9 arbovirus cohorts into 1 meta-cohort. Interested parties will be able to access data dictionaries that include information on variables across the data sets via Bio Studies. After consultation with each cohort, linked harmonized and curated human cohort data (CE and HDL) will be made accessible through the European Genome-phenome Archive platform to data users after their requests are evaluated by the ReCoDID Data Access Committee. This meta-cohort can facilitate various joint research projects (eg, on immunological interactions between sequential flavivirus infections and for the evaluation of potential biomarkers for severe arboviral disease).

Supporting Local Public Health and Planning Professionals to Implement Built Environment Changes: A Technical Assistance Program to Promote Physical Activity in Texas.

Built environment approaches that improve active transportation infrastructure and environmental design can increase physical activity. Funded by the Centers for Disease Control and Prevention, the Texas Department of State Health Services rejuvenated the Texas Plan4Health program from 2018 to 2023 to expand such approaches in Texas by providing technical assistance to teams of local public health professionals and planners to identify and implement projects connecting people to everyday destinations via active transport in their communities. However, the COVID-19 pandemic prompted Texas Plan4Health to modify the delivery of technical assistance to accommodate restrictions on travel and in-person gatherings. We used qualitative methods to conduct a postintervention process evaluation to describe the modified technical assistance process, understand the experiences of the 4 participating communities, and identify short-term outcomes and lessons learned. Texas Plan4Health helped communities overcome common barriers to built environment change, facilitated collaboration across community public health and planning professionals, and educated professionals about active transportation infrastructure and the relationship between their disciplines, thereby increasing community capacity to implement built environment improvements. This outcome, however, was mediated by the pre-existing resources and previous experiences with active transportation planning among the participating communities. Public health practitioners seeking to improve active transportation infrastructure and environmental design for physical activity should consider community-engaged approaches that advance partnership-building and collaborative experiential education among public health, planning, and other local government representatives, directing particular attention and additional training toward communities with fewer resources.

"I found out about Zika virus after she was born." Women's experiences of risk communication during the Zika virus epidemic in Brazil, Colombia, and Puerto Rico.

Providing accurate, evidence-based information to women with Zika infection during pregnancy was problematic because of the high degree of uncertainty in the diagnosis of the infection and the associated risk. The 2015-17 Zika virus epidemic overwhelmingly affected women in countries with limited access to safe abortion. Understanding women's perspectives on risk communication during pregnancy in the context of an emerging pathogen can help inform risk communication in response to future outbreaks that affect fetal or child development. We conducted a cross-sectional qualitative interview study with 73 women from 7 locations in Brazil, Colombia, and Puerto Rico to understand women's experiences of Zika virus (ZIKV) test and outcome-related communication during the ZIKV pandemic. We used thematic analysis to analyze the in-depth interviews. Participants in Brazil and Colombia reported that the healthcare system's lack of preparation and organization in communicating ZIKV test results and associated adverse outcomes led to their feeling abandoned and alone in confronting the challenges of a ZIKV-affected pregnancy. In contrast, participants in Puerto Rico reported that the regular testing schedules and clear, well-planned communication between the care team and between providers and pregnant women helped them to feel they could prepare for a ZIKV-affected pregnancy. Communication of the risk associated with an emerging pathogen suspected to affect pregnancy and developmental outcomes is a fraught issue. Public health authorities and healthcare providers should work together in the interpandemic period to understand families' preferences for risk communication during pregnancy in the presence of uncertainty and develop a community-informed plan for risk communication.

Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines.

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

How to plan and manage an individual participant data meta-analysis. An illustrative toolkit.

Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However, IPD-MAs are resource-intensive and require careful budgeting of time from data contributing groups, a dedicated management team, diversity of expertise, clearly documented data sharing and authorship agreements, and consistent and clear communication. We present a toolkit to facilitate the implementation and management of IPD-MAs, from study recruitment to retrospective harmonization. The toolkit was developed and refined over our work on multiple multinational IPD-MA projects over the last 13 years. The toolkit's budget and email templates, agreements, project management spreadsheets, and standard operating procedures are meant to facilitate routine IPD-MA tasks to expedite implementing and managing future IPD-MA projects.

Reconciling the biomedical data commons and the GDPR: three lessons from the EUCAN ELSI collaboratory.

The coming-into-force of the EU General Data Protection Regulation (GDPR) is a watershed moment in the legal recognition of enforceable rights to informational self-determination. The rapid evolution of legal requirements applicable to data use, however, has the potential to outstrip the capabilities of networks of biomedical data users to respond to the shifting norms. It can also delegitimate established institutional bodies that are responsible for assessing and authorising the downstream use of data, including research ethics committees and institutional data custodians. These burdens are especially pronounced for clinical and research networks that are of transnational scale, because the legal compliance burden for outbound international data transfers from the EEA is especially high. Legislatures, courts, and regulators in the EU should therefore implement the following three legal changes. First, the responsibilities of particular actors in a data sharing network should be delimited through the contractual allocation of responsibilities between collaborators. Second, the use of data through secure data processing environments should not trigger the international transfer provisions of the GDPR. Third, the use of federated data analysis methodologies that do not provide analysis nodes or downstream users access to identifiable personal data as part of the outputs of those analyses should not be considered circumstances of joint controllership, nor lead to the users of non-identifiable data to be considered controllers or processors. These small clarifications of, or modifications to, the GDPR would facilitate the exchange of biomedical data amongst clinicians and researchers.

Percepções das mulheres grávidas sobre as fontes de informação relativas ao vírus Zika: um estudo qualitativo / Pregnant women's perceptions on information sources on Zika virus: a qualitative study

Resumo A epidemia do vírus Zika (ZIKV) teve impacto sanitário, psicossocial e econômico sobre pessoas em idade reprodutiva. A principal preocupação foi a infecção durante a gravidez devido a possível transmissão vertical e sua associação com resultados fetais e infantis adversos, conhecida como síndrome congênita associada à infecção pelo Vírus Zika (SCZ). Este estudo qualitativo utiliza a fenomenologia e a teoria fundamentada. O estudo inclui entrevistas com 98 mulheres, parte grávida durante a epidemia de ZIKV no Brasil, Colômbia e Porto Rico e que tiveram filhos com SCZ ou sem comprometimento neurológico diagnosticado. Além disso, o estudo inclui um grupo de mulheres grávidas durante a pandemia de COVID-19 nos mesmos países. Em ambos os grupos, as entrevistadas tinham diferentes níveis de conhecimento sobre ZIKV. O estudo constatou que as mensagens veiculadas por meio da mídia eram alarmistas; em contraste com as informações fornecidas por profissionais de saúde, consideradas mais confiáveis. Mulheres gestantes durante a epidemia do ZIKV relataram ter recebido seu diagnóstico de infecção por ZIKV e SCZ tardiamente ou após o parto. O estudo destaca as necessidades das mulheres grávidas em cenários de alto risco, a importância de processos de educação em saúde e a necessidade de reforçar a comunicação e a educação continuada.

Abstract The Zika virus (ZIKV) epidemic had a sanitary, psychosocial, and economic impact on individuals of reproductive age. The primary concern revolved around infection during pregnancy due to possible vertical transmission and its association with adverse fetal and infant outcomes, known as Congenital Zika Syndrome (CZS). This qualitative study employs phenomenology and grounded theory. This study includes interviews with 98 women, some pregnant during the ZIKV epidemic in Brazil, Colombia, and Puerto Rico, who had children with CZS or without diagnosed neurological impairment. Additionally, the study included a group of women who were pregnant during the Covid-19 pandemic in these same countries. In both groups, interviewees had varying levels of knowledge about ZIKV. The study found that messages conveyed through the media tended to be alarmist, in contrast to the information provided by healthcare professionals, which was considered more trustworthy. Pregnant women during the ZIKV epidemic reported receiving their ZIKV and CSZ infection diagnoses late, either during or after childbirth. The study underscores the needs of pregnant women in high-risk scenarios, the importance of health education processes, and the necessity to reinforce communication and continuing education.

Application of Causal Inference Methods to Pooled Longitudinal Non- Randomized Studies: A Methodological Systematic Review.

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

FAIR, ethical, and coordinated data sharing for COVID-19 response: a scoping review and cross-sectional survey of COVID-19 data sharing platforms and registries.

Data sharing is central to the rapid translation of research into advances in clinical medicine and public health practice. In the context of COVID-19, there has been a rush to share data marked by an explosion of population-specific and discipline-specific resources for collecting, curating, and disseminating participant-level data. We conducted a scoping review and cross-sectional survey to identify and describe COVID-19-related platforms and registries that harmonise and share participant-level clinical, omics (eg, genomic and metabolomic data), imaging data, and metadata. We assess how these initiatives map to the best practices for the ethical and equitable management of data and the findable, accessible, interoperable, and reusable (FAIR) principles for data resources. We review gaps and redundancies in COVID-19 data-sharing efforts and provide recommendations to build on existing synergies that align with frameworks for effective and equitable data reuse. We identified 44 COVID-19-related registries and 20 platforms from the scoping review. Data-sharing resources were concentrated in high-income countries and siloed by comorbidity, body system, and data type. Resources for harmonising and sharing clinical data were less likely to implement FAIR principles than those sharing omics or imaging data. Our findings are that more data sharing does not equate to better data sharing, and the semantic and technical interoperability of platforms and registries harmonising and sharing COVID-19-related participant-level data needs to improve to facilitate the global collaboration required to address the COVID-19 crisis.

Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses.

BACKGROUND: Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building and evaluating diagnostic and prognostic models, making them an important tool for informing the research and public health responses to COVID-19. METHODS: We conducted a rapid systematic review of protocols and publications from planned, ongoing, or completed COVID-19-related IPD-MAs to identify areas of overlap and maximise data request and harmonisation efforts. We searched four databases using a combination of text and MeSH terms. Two independent reviewers determined eligibility at the title-abstract and full-text stages. Data were extracted by one reviewer into a pretested data extraction form and subsequently reviewed by a second reviewer. Data were analysed using a narrative synthesis approach. A formal risk of bias assessment was not conducted. RESULTS: We identified 31 COVID-19-related IPD-MAs, including five living IPD-MAs and ten IPD-MAs that limited their inference to published data (e.g., case reports). We found overlap in study designs, populations, exposures, and outcomes of interest. For example, 26 IPD-MAs included RCTs; 17 IPD-MAs were limited to hospitalised patients. Sixteen IPD-MAs focused on evaluating medical treatments, including six IPD-MAs for antivirals, four on antibodies, and two that evaluated convalescent plasma. CONCLUSIONS: Collaboration across related IPD-MAs can leverage limited resources and expertise by expediting the creation of cross-study participant-level data datasets, which can, in turn, fast-track evidence synthesis for the improved diagnosis and treatment of COVID-19. TRIAL REGISTRATION: 10.17605/OSF.IO/93GF2.

"How about me giving blood for the COVID vaccine and not being able to get vaccinated?" A cognitive interview study on understanding of and agreement with broad consent for future use of data and samples in Colombia and Nicaragua.

Broad consent for future use, wherein researchers ask participants for permission to share participant-level data and samples collected within the study for purposes loosely related to the study objectives, is central to enabling ethical data and sample reuse. Ensuring that participants understand broad consent-related language is key to maintaining trust in the study and public health research. We conducted 52 cognitive interviews to explore cohort research participants' and their parents' understanding of the broad consent-related language in the University of California at Berkeley template informed consent (IC) form for biomedical research. Participants and their parents were recruited from long-standing infectious disease cohort studies in Nicaragua and Colombia and interviewed during the COVID-19 pandemic. We conducted semi-structured interviews to assess participants' agreement with the key concepts in the IC after clarifying them through the cognitive interview. Participants did not understand abstract concepts, including collecting and reusing genetic data. Participants wanted to learn about incidental findings, future users and uses. Trust in the research team and the belief that sharing could lead to new vaccines or treatments were critical to participant support for data and sample sharing. Participants highlighted the importance of data and sample sharing for COVID-19 response and equitable access to vaccines and treatments developed through sharing. Our findings on participants' understanding of broad consent and preferences for data and sample sharing can help inform researchers and ethics review committees working to enable ethical and equitable data and sample sharing.

Adjusting for misclassification of an exposure in an individual participant data meta-analysis.

A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate unbiased estimation of adjusted and unadjusted exposure-outcome associations and between-study heterogeneity in IPD-MA, where the extent and nature of exposure misclassification may vary across studies. We present Bayesian methods that allow misclassification of binary exposure variables to depend on study- and participant-level characteristics. In an example of the differential diagnosis of dengue using two variables, where the gold standard measurement for the exposure variable was unavailable for some studies which only measured a surrogate prone to misclassification, our methods yielded more accurate estimates than analyses naive with regard to misclassification or based on gold standard measurements alone. In a simulation study, the evaluated misclassification model yielded valid estimates of the exposure-outcome association, and was more accurate than analyses restricted to gold standard measurements. Our proposed framework can appropriately account for the presence of binary exposure misclassification in IPD-MA. It requires that some studies supply IPD for the surrogate and gold standard exposure, and allows misclassification to follow a random effects distribution across studies conditional on observed covariates (and outcome). The proposed methods are most beneficial when few large studies that measured the gold standard are available, and when misclassification is frequent.

Heterogeneity of Zika virus exposure and outcome ascertainment across cohorts of pregnant women, their infants and their children: a metadata survey.

OBJECTIVES: To support the Zika virus (ZIKV) Individual Participant Data (IPD) Consortium's efforts to harmonise and analyse IPD from ZIKV-related prospective cohort studies and surveillance-based studies of pregnant women and their infants and children; we developed and disseminated a metadata survey among ZIKV-IPD Meta-Analysis (MA) study participants to identify and provide a comprehensive overview of study-level heterogeneity in exposure, outcome and covariate ascertainment and definitions. SETTING: Cohort and surveillance studies that measured ZIKV infection during pregnancy or at birth and measured fetal, infant, or child outcomes were identified through a systematic search and consultations with ZIKV researchers and Ministries of Health from 20 countries or territories. PARTICIPANTS: Fifty-four cohort or active surveillance studies shared deidentified data for the IPD-MA and completed the metadata survey, representing 33 061 women (11 020 with ZIKV) and 18 281 children. PRIMARY AND SECONDARY OUTCOME MEASURES: Study-level heterogeneity in exposure, outcome and covariate ascertainment and definitions. RESULTS: Median study sample size was 268 (IQR=100, 698). Inclusion criteria, follow-up procedures and exposure and outcome ascertainment were highly heterogenous, differing meaningfully across regions and multisite studies. Enrolment duration and follow-up for children after birth varied before and after the declaration of the Public Health Emergency of International Concern (PHEIC) and according to the type of funding received. CONCLUSION: This work highlights the logistic and statistical challenges that must be addressed to account for the multiple sources of within-study and between-study heterogeneity when conducting IPD-MAs of data collected in the research response to emergent pathogens like ZIKV.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

OBJECTIVE: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19. DESIGN: Two stage individual participant data meta-analysis. SETTING: Secondary and tertiary care. PARTICIPANTS: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021. DATA SOURCES: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ, and through PROSPERO, reference checking, and expert knowledge. MODEL SELECTION AND ELIGIBILITY CRITERIA: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor. METHODS: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters. MAIN OUTCOME MEASURES: 30 day mortality or in-hospital mortality. RESULTS: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28). CONCLUSION: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.

Neurodevelopment in Normocephalic Children Exposed to Zika Virus in Utero with No Observable Defects at Birth: A Systematic Review with Meta-Analysis.

Zika virus (ZIKV) infection during pregnancy is a cause of pregnancy loss and multiple clinical and neurological anomalies in children. This systematic review aimed to assess the effect of ZIKV exposure in utero on the long-term neurodevelopment of normocephalic children born to women with ZIKV infection in pregnancy. This review was conducted according to the PRISMA guidelines for systematic reviews and meta-analyses. We performed a random effects meta-analysis to estimate the cross-study prevalence of neurodevelopmental delays in children using the Bayley Scales for Infant and Toddler Development (BSID-III). The risk of bias was assessed using Cochrane's Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Full-text reviews were performed for 566 articles, and data were extracted from 22 articles corresponding to 20 studies. Nine articles including data from 476 children found 6.5% (95% CI: 4.1-9.3) of infants and children to have any type of non-language cognitive delay; 29.7% (95% CI: 21.7-38.2) to have language delay; and 11.5% (95% CI: 4.8-20.1) to have any type of motor delay. The pooled estimates had a high level of heterogeneity; thus, results should be interpreted with caution. Larger prospective studies that include a non-exposed control group are needed to confirm whether ZIKV exposure in utero is associated with adverse child neurodevelopmental outcomes.

Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies.

OBJECTIVES: Among ID studies seeking to make causal inferences and pooling individual-level longitudinal data from multiple infectious disease cohorts, we sought to assess what methods are being used, how those methods are being reported, and whether these factors have changed over time. STUDY DESIGN AND SETTING: Systematic review of longitudinal observational infectious disease studies pooling individual-level patient data from 2+ studies published in English in 2009, 2014, or 2019. This systematic review protocol is registered with PROSPERO (CRD42020204104). RESULTS: Our search yielded 1,462 unique articles. Of these, 16 were included in the final review. Our analysis showed a lack of causal inference methods and of clear reporting on methods and the required assumptions. CONCLUSION: There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.