Background As a number of vaccines for COVID-19 are given emergency use authorization by local health agencies and are being administered in multiple countries, it is crucial to gain public trust in these vaccines to ensure herd immunity through vaccination. One way to gauge public sentiment regarding vaccines for the goal of increasing vaccination rates is by analyzing social media such as Twitter. Objective The goal of this research was to understand public sentiment toward COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of 60 days when the vaccines were started in the United States. Using the combination of topic detection and sentiment analysis, we identified different types of concerns regarding vaccines that were expressed by different groups of the public on social media. Methods To better understand public sentiment, we collected tweets for exactly 60 days starting from December 16, 2020 that contained hashtags or keywords related to COVID-19 vaccines. We detected and analyzed different topics of discussion of these tweets as well as their emotional content. Vaccine topics were identified by nonnegative matrix factorization, and emotional content was identified using the Valence Aware Dictionary and sEntiment Reasoner sentiment analysis library as well as by using sentence bidirectional encoder representations from transformer embeddings and comparing the embedding to different emotions using cosine similarity. Results After removing all duplicates and retweets, 7,948,886 tweets were collected during the 60-day time period. Topic modeling resulted in 50 topics; of those, we selected 12 topics with the highest volume of tweets for analysis. Administration and access to vaccines were some of the major concerns of the public. Additionally, we classified the tweets in each topic into 1 of the 5 emotions and found fear to be the leading emotion in the tweets, followed by joy. Conclusions This research focused not only on negative emotions that may have led to vaccine hesitancy but also on positive emotions toward the vaccine. By identifying both positive and negative emotions, we were able to identify the public's response to the vaccines overall and to news events related to the vaccines. These results are useful for developing plans for disseminating authoritative health information and for better communication to build understanding and trust.

Atualmente, o Sars-COV-2 se encontra disseminado por uma vasta área geográfica no mundo. A trajetória da pandemia após cruzar as fronteiras do território brasileiro (terrestre e litorânea), acompanhada de uma avaliação das medidas adotadas para sua contenção e os principais conflitos observados e apresentados no presente estudo, cumpre o objetivo de apontar questões atuais e futuras de políticas públicas para o enfrentamento da pandemia nas fronteiras brasileiras. Os resultados das análises realizadas demonstram que as áreas de maior concentração e adensamento populacional urbanos foram as mais afetadas pela contaminação do vírus. No entanto, a Covid-19 não poupou municípios menores, o que se observa pelo seu alastramento no território seguindo os caminhos da mobilidade rodoviária, fluvial e aérea no interior do Brasil. Sobre seu reflexo na área de fronteira, observa-se tanto um conflito interfederativo, com um quadro de descompasso entre medidas do governo federal e unidades subnacionais, quanto a inexistência de diálogos e acordos com os países vizinhos. Como sugestões, apontam-se a criação de instrumentos, protocolos, medidas e mecanismos para o enfrentamento da crise da pandemia da Covid-19 em áreas de fronteira terrestre e litorânea do Brasil.

Resumo: O Programa Territórios da Cidadania (PTC) é uma das mais relevantes políticas de desenvolvimento territorial vigentes no Brasil, principalmente no que tange sua abrangência e importância. Trata-se de uma política pública social que apresenta escopo diferenciado, com enfoque territorial, gestão social e interministerial. Apesar de o PTC ser oriundo de um processo evolutivo de políticas públicas como: Programa Nacional de Fortalecimento da Agricultura Familiar (Pronaf) e Programa de Desenvolvimento Sustentável dos Territórios Rurais (Pronat), este ainda apresenta certos gargalos, como a definição de critérios para a escolha dos territórios. Neste sentido, o artigo apresenta metodologia estatística com o objetivo de avaliar os critérios de elegibilidade e o grau de importância desses critérios para que um município seja atendido pelo programa, a partir de indicadores proxies aos critérios definidos em decreto. Como resultado, critérios como densidade demográfica, existência de quilombos e população indígena não apresentaram o protagonismo esperado. Já o Índice de Desenvolvimento Humano apresentou-se como principal critério de elegibilidade, mostrando que o indicador se mantém relevante para o ciclo de monitoramento e avaliação de políticas públicas brasileiras. A agricultura familiar, um dos principais pilares do PTC e de seus programas antecessores, também se mostrou importante, mantendo a coerência do escopo e objetivos do programa. Palavras-chaves:

Discute a disseminação da Covid-19 a partir da reflexão sobre o direito à moradia no Brasil, apresentando, entre outras coisas, uma análise sobre o tema utilizando-se dados do censo demográfico de 2010 (, 2011), dados preliminares do censo de 2019 (, 2019), além de dados da Fundação Oswaldo Cruz (Fiocruz) sobre a Covid-19 de 31 de julho de 2020 (Fiocruz, 2020).

BACKGROUND As a number of vaccines for COVID-19 are given emergency use authorization by local health agencies and are being administered in multiple countries, it is crucial to gain public trust in these vaccines to ensure herd immunity through vaccination. One way to gauge public sentiment regarding vaccines for the goal of increasing vaccination rates is by analyzing social media such as Twitter. OBJECTIVE The goal of this research was to understand public sentiment toward COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of 60 days when the vaccines were started in the United States. Using the combination of topic detection and sentiment analysis, we identified different types of concerns regarding vaccines that were expressed by different groups of the public on social media. METHODS To better understand public sentiment, we collected tweets for exactly 60 days starting from December 16, 2020 that contained hashtags or keywords related to COVID-19 vaccines. We detected and analyzed different topics of discussion of these tweets as well as their emotional content. Vaccine topics were identified by nonnegative matrix factorization, and emotional content was identified using the Valence Aware Dictionary and sEntiment Reasoner sentiment analysis library as well as by using sentence bidirectional encoder representations from transformer embeddings and comparing the embedding to different emotions using cosine similarity. RESULTS After removing all duplicates and retweets, 7,948,886 tweets were collected during the 60-day time period. Topic modeling resulted in 50 topics; of those, we selected 12 topics with the highest volume of tweets for analysis. Administration and access to vaccines were some of the major concerns of the public. Additionally, we classified the tweets in each topic into 1 of the 5 emotions and found fear to be the leading emotion in the tweets, followed by joy. CONCLUSIONS This research focused not only on negative emotions that may have led to vaccine hesitancy but also on positive emotions toward the vaccine. By identifying both positive and negative emotions, we were able to identify the public's response to the vaccines overall and to news events related to the vaccines. These results are useful for developing plans for disseminating authoritative health information and for better communication to build understanding and trust.