Public health response to COVID-19: the forecaster's dilemma

Virus-like structures for combination antigen protein mRNA vaccination

Improved vaccination requires better delivery of antigens and activation of the natural immune response. Here we report a lipid nanoparticle system with the capacity to carry antigens, including mRNA and proteins, which is formed into a virus-like structure by surface decoration with spike proteins, demonstrating application against SARS-CoV-2 variants. The strategy uses S1 protein from Omicron BA.1 on the surface to deliver mRNA of S1 protein from XBB.1. The virus-like particle enables specific augmentation of mRNAs expressed in human respiratory epithelial cells and macrophages via the interaction the surface S1 protein with ACE2 or DC-SIGN receptors. Activation of macrophages and dendritic cells is demonstrated by the same receptor binding. The combination of protein and mRNA increases the antibody response in BALB/c mice compared with mRNA and protein vaccines alone. Our exploration of the mechanism of this robust immunity suggests it might involve cross-presentation to diverse subsets of dendritic cells ranging from activated innate immune signals to adaptive immune signals.

Forecasting Seasonal Acute Malnutrition: Setting the Framework

BACKGROUND

Malnutrition is an umbrella term that refers to an impairment in nutrition indicative of subsequently compromised human well-being. The term covers the full spectrum of nutritional impairments from a small yet detectable departure from a "norm" to a terminal stage when severe malnutrition could result in death. This broad spectrum of nutritional departures from "the optimum" dictates the need for an ensemble of metrics to capture the complexity of involved mechanisms, risk factors, precipitating events, short-term, and long-term consequences. Ideally, these metrics should be universally applicable to vulnerable populations, settings, ages, and times when people are most susceptible to malnutrition. We should be able to characterize and intervene to minimize the risk of malnutrition, especially child acute malnutrition that could be assessed by anthropometric measurements.

OBJECTIVES

The main challenge in reaching such an ambitious goal is the complexity of measuring, characterizing, explaining, predicting, and preventing malnutrition at any dimension: temporal or spatial and at any scale: a person or a group. The expansive body of literature has been accumulated on many temporal aspects of malnutrition and seasonal changes in nutritional (anthropometric) status. The research community is now shifting their attention to predictive modeling of child malnutrition and its importance for clinical and public health interventions. This communication aims to provide an overview of challenges for understanding child malnutrition from a perspective of predictive modeling focusing on well-documented seasonal variations in nutritional outcomes and exploring "the systems approach" to tackle underlining conceptual and practical complexities to forecast seasonal malnutrition in an accurate and timely manner. This generalized approach to forecasting seasonal malnutrition is then applied specifically to child acute malnutrition.

Satisfaction with Telepsychiatry during the COVID-19 pandemic: Patients' and psychiatrists' report from a University Hospital

BACKGROUND

The COVID-19 pandemic has led to important changes in the approach to patients worldwide. Different agencies have proposed and implemented telemedicine-based care services in order to ensure access to health care for all people.

AIM

The aim of this study was to determine the satisfaction of patients using the Telepsychiatry service offered by the Department of Psychiatry of the Hospital de Clínicas (National University of Asunción, Paraguay).

METHODS

A cross sectional and descriptive study has been conducted. Participants were recruited through a phone-based survey. Satisfaction with Telepsychiatry has been measured with an adapted version of a satisfaction survey in Teleneurology. As a complement, psychiatrists from the Hospital de Clínicas were also interviewed about their rate of satisfaction with Telepsychiatry.

RESULTS

A total of 530 patients were included, 51.3% of whom were women. The consultation satisfaction scale ranged between 2.15 and 4.30 with a mean score of 3.02 ± 0.32. Cronbach's alpha for the scale was .897, indicating a good internal consistency. Patients' satisfaction was higher for the perception of Telepsychiatry and lower for the doctor-patient relationship. Of the physicians, 87.5% were satisfied with the Telepsychiatry service.

CONCLUSION

The satisfaction overall score indicates patients' general satisfaction with the quality of care in Telepsychiatry, mainly regarding the perception of health care. and lower satisfaction with the doctor-patient relationship. Nine out of 10 psychiatrists felt satisfied with the Telepsychiatry service and considered that the degree of patient's satisfaction was acceptable during the Telepsychiatry consultation.

The Impact of Emotion and Government Trust on Individuals' Risk Information Seeking and Avoidance during the COVID-19 Pandemic: A Cross-country Comparison

This study examines the emotional mechanisms of how public trust in the governments' actions to address the COVID-19 pandemic shapes individuals' risk information-seeking and avoidance. To make cross-cultural comparisons, we conducted a multi-country survey early in the pandemic in South Korea, the United States (US) and Singapore. The results suggest that trust was negatively related to fear, anger, sadness and anxiety, and positively related to hope. These emotions were significant mediators of the effect of trust on information seeking and avoidance, except for anger on avoidance. Importantly, the indirect effects of trust in government varied by country. Fear was a stronger mediator between trust and information seeking in South Korea than in the US. In contrast, sadness and anger played more prominent mediating roles in Singapore than in South Korea. This study offers theoretical insights into better understanding the roles of discrete emotions in forming information behaviors. The findings of this study also inform communication strategies that seek to navigate trust in managing pandemics that impact multiple nations.

Bayesian spatiotemporal forecasting and mapping of COVID-19 risk with application to West Java Province, Indonesia

The coronavirus disease (COVID-19) has spread rapidly to multiple countries including Indonesia. Mapping its spatiotemporal pattern and forecasting (small area) outbreaks are crucial for containment and mitigation strategies. Hence, we introduce a parsimonious space-time model of new infections that yields accurate forecasts but only requires information regarding the number of incidences and population size per geographical unit and time period. Model parsimony is important because of limited knowledge regarding the causes of COVID-19 and the need for rapid action to control outbreaks. We outline the basics of Bayesian estimation, forecasting, and mapping, in particular for the identification of hotspots. The methodology is applied to county-level data of West Java Province, Indonesia.