Changes in high-risk sexual behavior, HIV and other STI testing, and PrEP use during the COVID-19 pandemic in a longitudinal cohort of adolescent men who have sex with men 13 to 18 years old in the United States.

The COVID-19 pandemic has disrupted sexual health services among those most vulnerable to HIV acquisition, such as adolescent men who have sex with men (AMSM). We sought to characterize the changes in sexual-risk behaviors, HIV and other STI testing, and pre-exposure prophylaxis (PrEP) use among a longitudinal cohort of AMSM aged 13 to 18 years before and during the COVID-19 pandemic. We observed a significant decline in HIV testing and a marginal decrease in other STI testing since the pandemic began in March 2020. Outreach efforts and innovative remote delivery of sexual health services are needed to support access to healthcare services among AMSM as the pandemic persists.

RESUMEN: La pandemia de COVID-19 ha afectado la prestación de servicios de salud sexual para los más vulnerables, tales como los hombres adolescentes que tienen relaciones sexuales con hombres (AMSM; por sus siglas en ingles). En una cohorte longitudinal de AMSM de 13 a 18 años, examinamos los cambios en comportamientos sexuales de alto riesgo, la prueba de VIH, las pruebas de otras enfermedades de transmisión sexual, y el uso de Profilaxis Preexposición (PrEP) para el VIH antes y durante la pandemia. Desde el inicio de la pandemia en marzo de 2020, observamos una disminución significativa en la frecuencia de pruebas de VIH y una disminución marginal en la frecuencia de pruebas de otras enfermedades de transmisión sexual. Mientras persista la pandemia, serán necesarios más esfuerzos de divulgación e innovaciones en la prestación remota de servicios de salud sexual para apoyar el acceso a dichos servicios por parte de AMSM.

Approaches to education policies on the global scene of the post-COVID 19 pandemic

The COVID 19 pandemic had an unusual multidimensional impact on humanity as a whole, creating or recreating new or renewed forms of relationship between people, communities and the state, as an articulating entity of social relations and spaces of human development. In this context, the general use of ICTs in teaching-learning processes at all levels of the educational system is common, to the detriment of the person-to-person encounter affected by social distancing. The objective of the article is to describe a useful conceptual framework to redefine educational policies in accordance with the new realities that characterize post-pandemic scenarios in Ecuador. Methodologically it is a documentary, analytical and prospective research. The authors conclude that investment in education is considered urgent since its material and symbolic spaces mean for the majority of young people the most legitimate opportunity to train, achieve better opportunities and ascend socially, a situation that reduces the dynamics of social conflict.

POLICY FOR THE DEVELOPMENT OF CUSTOM VILLAGES INTO A DIGITAL-BASED TOURISM VILLAGE THAT CAN ADAPT TO THE NEW NORMAL ERA (CASE STUDY OF CUSTOM VILLAGES IN BALI, INDONESIA)

The province of Bali, which relies on tourism as a driving force for the economy, is certainly very affected by the COVID-19 pandemic. The decline in foreign tourist arrivals to Bali has made the government and tourism actors begin to look at domestic tourists. Given the existence of tourism sector workers who return to the village, the development of tourist villages through the participation of local communities is very potential to be developed. The purpose of this research is to develop a policy framework for the development of custom villages as digital-based tourism villages that are able to adapt to the new normal era. This study used a MULTIPOL prospective analysis, where data were collected through FGDs. The policies analyzed are tourism village policies and digital villages, both in supply side and demand side scenarios. The results show that in the tourism village policy, the program arrangement of tourist objects/attractions is a priority. Meanwhile, in digital village policies, the development and improvement of information network programs are important.

What are the underlying transmission patterns of COVID-19 outbreak? An age-specific social contact characterization.

BACKGROUND: COVID-19 has spread to 6 continents. Now is opportune to gain a deeper understanding of what may have happened. The findings can help inform mitigation strategies in the disease-affected countries. METHODS: In this work, we examine an essential factor that characterizes the disease transmission patterns: the interactions among people. We develop a computational model to reveal the interactions in terms of the social contact patterns among the population of different age-groups. We divide a city's population into seven age-groups: 0-6 years old (children); 7-14 (primary and junior high school students); 15-17 (high school students); 18-22 (university students); 23-44 (young/middle-aged people); 45-64 years old (middle-aged/elderly people); and 65 or above (elderly people). We consider four representative settings of social contacts that may cause the disease spread: (1) individual households; (2) schools, including primary/high schools as well as colleges and universities; (3) various physical workplaces; and (4) public places and communities where people can gather, such as stadiums, markets, squares, and organized tours. A contact matrix is computed to describe the contact intensity between different age-groups in each of the four settings. By integrating the four contact matrices with the next-generation matrix, we quantitatively characterize the underlying transmission patterns of COVID-19 among different populations. FINDINGS: We focus our study on 6 representative cities in China: Wuhan, the epicenter of COVID-19 in China, together with Beijing, Tianjin, Hangzhou, Suzhou, and Shenzhen, which are five major cities from three key economic zones. The results show that the social contact-based analysis can readily explain the underlying disease transmission patterns as well as the associated risks (including both confirmed and unconfirmed cases). In Wuhan, the age-groups involving relatively intensive contacts in households and public/communities are dispersedly distributed. This can explain why the transmission of COVID-19 in the early stage mainly took place in public places and families in Wuhan. We estimate that Feb. 11, 2020 was the date with the highest transmission risk in Wuhan, which is consistent with the actual peak period of the reported case number (Feb. 4-14). Moreover, the surge in the number of new cases reported on Feb. 12 and 13 in Wuhan can readily be captured using our model, showing its ability in forecasting the potential/unconfirmed cases. We further estimate the disease transmission risks associated with different work resumption plans in these cities after the outbreak. The estimation results are consistent with the actual situations in the cities with relatively lenient policies, such as Beijing, and those with strict policies, such as Shenzhen. INTERPRETATION: With an in-depth characterization of age-specific social contact-based transmission, the retrospective and prospective situations of the disease outbreak, including the past and future transmission risks, the effectiveness of different interventions, and the disease transmission risks of restoring normal social activities, are computationally analyzed and reasonably explained. The conclusions drawn from the study not only provide a comprehensive explanation of the underlying COVID-19 transmission patterns in China, but more importantly, offer the social contact-based risk analysis methods that can readily be applied to guide intervention planning and operational responses in other countries, so that the impact of COVID-19 pandemic can be strategically mitigated. FUNDING: General Research Fund of the Hong Kong Research Grants Council; Key Project Grants of the National Natural Science Foundation of China.