'We dry contaminated meat to make it safe': An assessment of knowledge, attitude and practices on anthrax during an outbreak, Kisumu, Kenya, 2019.

INTRODUCTION: Anthrax is the highest-ranked priority zoonotic disease in Kenya with about ten human cases annually. Anthrax outbreak was reported in Kisumu East Sub County after some villagers slaughtered and ate beef from a cow suspected to have died of anthrax. We aimed at establishing the magnitude of the outbreak, described associated factors, and assessed community knowledge, attitude, and practices on anthrax. METHODS: We reviewed human and animal records, conducted case search and contact tracing using standard case definitions in the period from July 1through to July 28, 2019. A cross-sectional study was conducted to assess community knowledge, attitude, and practices towards anthrax. The household selection was done using multistage sampling. We cleaned and analyzed data in Ms. Excel and Epi Info. Descriptive statistics were carried out for continuous and categorical variables while analytical statistics for the association between dependent and independent variables were calculated. RESULTS: Out of 53 persons exposed through consumption or contact with suspicious beef, 23 cases (confirmed: 1, probable: 4, suspected: 18) were reviewed. The proportion of females was 52.17% (12/23), median age 13.5 years and range 45 years. The attack rate was 43.4% (23/53) and the case fatality rate was 4.35% (1/23). Knowledge level, determined by dividing those considered to be 'having good knowledge' on anthrax (numerator) by the total number of respondents (denominator) in the population regarding cause, transmission, symptoms and prevention was 51% for human anthrax and 52% for animal anthrax. Having good knowledge on anthrax was associated with rural residence [OR = 5.5 (95% CI 2.1-14.4; p<0.001)], having seen a case of anthrax [OR = 6.2 (95% CI 2.8-14.2; p<0.001)] and among those who present cattle for vaccination [OR = 2.6 (95% CI 1.2-5.6; p = 0.02)]. About 23.2% (26/112) would slaughter and sell beef to neighbors while 63.4% (71/112) would bury or burn the carcass. Nearly 93.8% (105/112) believed vaccination prevents anthrax. However, 5.4% (62/112) present livestock for vaccination. CONCLUSION: Most anthrax exposures were through meat consumption. Poor knowledge of the disease might hamper prevention and control efforts.

Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events.

BACKGROUND: Social media allows researchers to study opinions and reactions to events in real time. One area needing more study is anthrax-related events. A computational framework that utilizes machine learning techniques was created to collect tweets discussing anthrax, further categorize them as relevant by the month of data collection, and detect discussions on anthrax-related events. OBJECTIVE: The objective of this study was to detect discussions on anthrax-related events and to determine the relevance of the tweets and topics of discussion over 12 months of data collection. METHODS: This is an infoveillance study, using tweets in English containing the keyword "Anthrax" and "Bacillus anthracis", collected from September 25, 2017, through August 15, 2018. Machine learning techniques were used to determine what people were tweeting about anthrax. Data over time was plotted to determine whether an event was detected (a 3-fold spike in tweets). A machine learning classifier was created to categorize tweets by relevance to anthrax. Relevant tweets by month were examined using a topic modeling approach to determine the topics of discussion over time and how these events influence that discussion. RESULTS: Over the 12 months of data collection, a total of 204,008 tweets were collected. Logistic regression analysis revealed the best performance for relevance (precision=0.81; recall=0.81; F1-score=0.80). In total, 26 topics were associated with anthrax-related events, tweets that were highly retweeted, natural outbreaks, and news stories. CONCLUSIONS: This study shows that tweets related to anthrax can be collected and analyzed over time to determine what people are discussing and to detect key anthrax-related events. Future studies are required to focus only on opinion tweets, use the methodology to study other terrorism events, or to monitor for terrorism threats.