Background: During the COVID-19 pandemic, there is a heightened need to understand health information seeking behaviors to address disparities in knowledge and beliefs about the crisis.Objective: This study assessed sociodemographic predictors of the use and trust of different COVID-19 information sources, as well as the association between information sources and knowledge and beliefs about the pandemic.Methods: An online survey was conducted among US adults in two rounds during March and April 2020 using advertisement-based recruitment on social media. Participants were asked about their use of 11 different COVID-19 information sources as well as their most trusted source of information. The selection of COVID-related knowledge and belief questions was based on past empirical literature and salient concerns at the time of survey implementation.Results: The sample consisted of 11,242 participants. When combined, traditional media sources (television, radio, podcasts, or newspapers) were the largest sources of COVID-19 information (91.2%). Among those using mainstream media sources for COVID-19 information (n=7811, 69.5%), popular outlets included CNN (24.0%), Fox News (19.3%), and other local or national networks (35.2%). The largest individual information source was government websites (87.6%). They were also the most trusted source of information (43.3%), although the odds of trusting government websites were lower among males (adjusted odds ratio [AOR] 0.58, 95% CI 0.53-0.63) and those aged 40-59 years and ≥60 years compared to those aged 18-39 years (AOR 0.83, 95% CI 0.74-0.92; AOR 0.62, 95% CI 0.54-0.71). Participants used an average of 6.1 sources (SD 2.3). Participants who were male, aged 40-59 years or ≥60 years; not working, unemployed, or retired; or Republican were likely to use fewer sources while those with children and higher educational attainment were likely to use more sources. Participants surveyed in April were markedly less likely to use (AOR 0.41, 95% CI 0.35-0.46) and trust (AOR 0.51, 95% CI 0.47-0.56) government sources. The association between information source and COVID-19 knowledge was mixed, while many COVID-19 beliefs were significantly predicted by information source; similar trends were observed with reliance on different types of mainstream media outlets.Conclusions: COVID-19 information source was significantly determined by participant sociodemographic characteristics and was also associated with both knowledge and beliefs about the pandemic. Study findings can help inform COVID-19 health communication campaigns and highlight the impact of using a variety of different and trusted information sources.

The global spread and the increased frequency and magnitude of epidemic dengue in the last 50 years underscore the urgent need for effective tools for surveillance, prevention, and control. This review aims at providing a systematic overview of what predictors are critical and which spatial and spatio-temporal modeling approaches are useful in generating risk maps for dengue. A systematic search was undertaken, using the PubMed, Web of Science, WHOLIS, Centers for Disease Control and Prevention (CDC) and OvidSP databases for published citations, without language or time restrictions. A manual search of the titles and abstracts was carried out using predefined criteria, notably the inclusion of dengue cases. Data were extracted for pre-identified variables, including the type of predictors and the type of modeling approach used for risk mapping. A wide variety of both predictors and modeling approaches was used to create dengue risk maps. No specific patterns could be identified in the combination of predictors or models across studies. The most important and commonly used predictors for the category of demographic and socio-economic variables were age, gender, education, housing conditions and level of income. Among environmental variables, precipitation and air temperature were often significant predictors. Remote sensing provided a source of varied land cover data that could act as a proxy for other predictor categories. Descriptive maps showing dengue case hotspots were useful for identifying high-risk areas. Predictive maps based on more complex methodology facilitated advanced data analysis and visualization, but their applicability in public health contexts remains to be established. The majority of available dengue risk maps was descriptive and based on retrospective data. Availability of resources, feasibility of acquisition, quality of data, alongside available technical expertise, determines the accuracy of dengue risk maps and their applicability to the field of public health. A large number of unknowns, including effective entomological predictors, genetic diversity of circulating viruses, population serological profile, and human mobility, continue to pose challenges and to limit the ability to produce accurate and effective risk maps, and fail to support the development of early warning systems.

Globally, dengue, Zika virus, and chikungunya are important viral mosquito-borne diseases that infect millions of people annually. Their geographic range includes not only tropical areas but also sub-tropical and temperate zones such as Japan and Italy. The relative severity of these arboviral disease outbreaks can vary depending on the setting. In this study we explore variation in the epidemiologic potential of outbreaks amongst these climatic zones and arboviruses in order to elucidate potential reasons behind such differences. We reviewed the peer-reviewed literature (PubMed) to obtain basic reproduction number (R0) estimates for dengue, Zika virus, and chikungunya from tropical, sub-tropical and temperate regions. We also computed R0 estimates for temperate and sub-tropical climate zones, based on the outbreak curves in the initial outbreak phase. Lastly we compared these estimates across climate zones, defined by latitude. Of 2115 studies, we reviewed the full text of 128 studies and included 65 studies in our analysis. Our results suggest that the R0 of an arboviral outbreak depends on climate zone, with lower R0 estimates, on average, in temperate zones (R0 = 2.03) compared to tropical (R0 = 3.44) and sub-tropical zones (R0 = 10.29). The variation in R0 was considerable, ranging from 0.16 to 65. The largest R0 was for dengue (65) and was estimated by the Ross-Macdonald model in the tropical zone, whereas the smallest R0 (0.16) was for Zika virus and was estimated statistically from an outbreak curve in the sub-tropical zone. The results indicate climate zone to be an important determinant of the basic reproduction number, R0, for dengue, Zika virus, and chikungunya. The role of other factors as determinants of R0, such as methods, environmental and social conditions, and disease control, should be further investigated. The results suggest that R0 may increase in temperate regions in response to global warming, and highlight the increasing need for strengthening preparedness and control activities.

Low and middle income countries face many challenges in meeting their populations’ mental health care needs. Though family caregiving is crucial to the management of severe mental health disabilities, such as schizophrenia, the economic costs borne by family caregivers often go unnoticed. In this study, we estimated the household economic costs of schizophrenia and quality of life of family caregivers in Ghana. We used a cost of illness analysis approach. Quality of life (QoL) was assessed using the abridged WHO Quality of Life (WHOQOL-BREF) tool. Cross-sectional data were collected from 442 caregivers of patients diagnosed with schizophrenia at least six months prior to the study and who received consultation in any of the three psychiatric hospitals in Ghana. Economic costs were categorized as direct costs (including medical and non-medical costs of seeking care), indirect costs (productivity losses to caregivers) and intangible costs (non-monetary costs such as stigma and pain). Direct costs included costs of medical supplies, consultations, and travel. Indirect costs were estimated as value of productive time lost (in hours) to primary caregivers. Intangible costs were assessed using the Zarit Burden Interview (ZBI). We employed multiple regression models to assess the covariates of costs, caregiver burden, and QoL. Total monthly cost to caregivers was US$ 273.28, on average. Key drivers of direct costs were medications (50%) and transportation (27%). Direct costs per caregiver represented 31% of the reported monthly earnings. Mean caregiver burden (measured by the ZBI) was 16.95 on a scale of 0–48, with 49% of caregivers reporting high burden. Mean QoL of caregivers was 28.2 (range: 19.6–34.8) out of 100. Better educated caregivers reported lower indirect costs and better QoL. Caregivers with higher severity of depression, anxiety and stress reported higher caregiver burden and lower QoL. Males reported better QoL. These findings highlight the high household burden of caregiving for people living with schizophrenia in low income settings. Results underscore the need for policies and programs to support caregivers.

A severe neurological disorder, Guillain-Barré syndrome (GBS) is the leading cause of acute flaccid paralysis. Enhanced surveillance of GBS in Latin America and the Caribbean (LAC) following the 2015–2016 Zika virus (ZIKV) epidemic presents an opportunity to estimate, for the first time, the regional incidence of GBS. For this systematic review and meta-analysis, we searched nine scientific databases and grey literature from January 1, 1980 to October 1, 2018. Sources with primary data on incident GBS cases in LAC within a well-defined population and timeframe, published in English, Spanish, Portuguese, or French, were included. We calculated the annual GBS incidence rates (IRs) and 95% confidence intervals (CIs) for each source based on published data. Following an assessment of heterogeneity, we used random-effects meta-analysis to calculate the pooled annual IR of GBS. The study is registered with PROSPERO, number CRD42018086659. Of the 6586 initial citation hits, 31 were eligible for inclusion. Background annual GBS IRs in Latin America ranged from 0.40 in Brazil to 2.12/100,000 in Chile. The pooled annual IR in the Caribbean was 1.64 (95% CI 1.29–2.12, I²<0.01, p = 0.44). During the ZIKV epidemic, GBS IRs ranged from 0.62 in Mexico to 9.35/100,000 in Martinique. GBS increased 2.6 (95% CI 2.3–2.9) times during ZIKV and 1.9 (95% CI 1.1–3.4) times during chikungunya outbreaks over background rates. A limitation of this review is that the studies included employed different methodologies to find and ascertain cases of GBS, which could contribute to IR heterogeneity. In addition, it is important to consider that data on GBS are lacking for many countries in the region. Background IRs of GBS appear to peak during arboviral disease outbreaks. The current review contributes to an understanding of the epidemiology of GBS in the LAC region, which can inform healthcare system planning and preparedness, particularly during arboviral epidemics. Registered with PROSPERO: CRD42018086659. A severe neurological disorder, Guillain-Barré syndrome (GBS) is the leading cause of acute flaccid paralysis. This is the first systematic review on GBS incidence in Latin America and the Caribbean before and during arboviral disease outbreaks. There is a large sub-regional and annual fluctuation in the incidence of GBS. Background annual GBS incidence rates (IRs) in Latin America ranged from 0.40 in Brazil to 2.12/100,000 in Chile. The pooled annual IR in the Caribbean was 1.64 (95% CI 1.29–2.12, I²<0.01, p = 0.44). During the ZIKV epidemic, GBS IRs ranged from 0.62 in Mexico to 9.35/100,000 in Martinique. GBS increased 2.9 times during ZIKV and 1.9 times during chikungunya outbreaks over background rates. GBS is a costly disease, which can result in long-term disability and high mortality rates in resource constrained healthcare settings. Because GBS can be triggered by arboviral infections, baseline incidence of GBS is critical for detecting neglected tropical disease outbreaks. The current review contributes to an understanding of the epidemiology of GBS in the LAC region, which can inform healthcare system planning and preparedness.

Dengue is the major public health burden in Sri Lanka. Kalutara is one of the highly affected districts. Understanding the drivers of dengue is vital in controlling and preventing the disease spread. This study focuses on quantifying the influence of weather variability on dengue incidence over 10 Medical Officer of Health (MOH) divisions of Kalutara district. Weekly weather variables and data on dengue notifications, measured at 10 MOH divisions in Kalutara from 2009 to 2013, were retrieved and analysed. Distributed lag non-linear model and hierarchical-analysis was used to estimate division specific and overall relationships between weather and dengue. We incorporated lag times up to 12 weeks and evaluated models based on the Akaike Information Criterion. Consistent exposure-response patterns between different geographical locations were observed for rainfall, showing increasing relative risk of dengue with increasing rainfall from 50 mm per week. The strongest association with dengue risk centred around 6 to 10 weeks following rainfalls of more than 300 mm per week. With increasing temperature, the overall relative risk of dengue increased steadily starting from a lag of 4 weeks. We found similarly a strong link between the Oceanic Niño Index to weather patterns in the district in Sri Lanka and to dengue at a longer latency time confirming these relationships. Part of the influences of rainfall and temperature can be seen as mediator in the causal pathway of the Ocean Niño Index, which may allow a longer lead time for early warning signals. Our findings describe a strong association between weather, El Niño-Southern Oscillation and dengue in Sri Lanka.