Back

SARS-CoV-2 seroprevalence, vaccination, and hesitancy in agricultural workers in Guatemala

Calvimontes, D. M.; Krisher, L.; Cruz-Aguilar, A.; Pilloni-Alessio, D.; Crisostomo-Cal, L. E.; Castaneda-Sosa, E. A.; Butler-Dawson, J.; Olson, D.; Newman, L. S.; Asturias, E. J.

2022-02-24 infectious diseases
10.1101/2022.02.22.22270907 medRxiv
Show abstract

BackgroundDuring the COVID-19 pandemic, serological tests to screen populations have provided better estimates of the cumulative incidence of infection. This study evaluated the seroprevalence of SARS-CoV-2 in agricultural workers in rural Guatemala, their COVID-19 vaccine uptake and vaccination attitudes. MethodsA cross-sectional study was undertaken from August to November of 2021, in agricultural workers at a sugar plantation in Guatemala. A questionnaire was used to collect demographic, previous COVID-19 infection, vaccination, and attitudes toward vaccination. Serological testing was performed to detect SARS-CoV-2 IgM and IgG. ResultsOf the 4,343 study participants, 1,279 (29.4%) were seropositive for SARS-CoV-2 compared to 2.3% who reported previous COVID-19 infection. COVID-19 vaccine coverage was 85% for the first dose and 21.9% for second dose. Vaccine refusal was 0.6%, and 13.9% expressed some degree of vaccine hesitancy. Vaccine hesitant workers or those refusing were less likely to have had the COVID-19 vaccine. Main reasons to get the vaccine were to protect family, coworkers, and community. ConclusionAgricultural workers in countries like Guatemala have suffered a high incidence of asymptomatic and undetected SARS-CoV-2 infection. Most have received the COVID-19 vaccine, but there are moderate degrees of vaccine hesitancy that require better public health information to overcome it.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.