School-aged children play a major role in the transmission of many respiratory pathogens due to high rate of close contacts in schools. The validity and accuracy of proxy-reported contact data may be limited, particularly for children when attending school. We observed social contacts within schools and assessed the accuracy of proxy-reported versus observed physical contact data among students in rural Gambia.
We enrolled school children who had also been recruited to a survey of Streptococcus pneumoniae carriage and social contacts. We visited participants at school and observed their contact patterns within and outside the classroom for two hours. We recorded the contact type, gender and approximate age of the contactee, and class size. We calculated age-stratified contact matrices to determine in-school contact patterns. We compared proxy-reported estimated physical contacts for the subset of participants (18 %) randomised to be observed on the same day for which the parent or caregiver reported the school contacts.
We recorded 3822 contacts for 219 participants from 114 schools. The median number of contacts was 15 (IQR: 11–20). Contact patterns were strongly age-assortative, and mainly involved physical touch (67.5 %). Those aged 5–9 years had the highest mean number of contacts [19.0 (95 %CI: 16.7–21.3)] while the ≥ 15-year age group had fewer contacts [12.8 (95 %CI: 10.9–14.7)]. Forty (18 %) participants had their school-observed contact data collected on the same day as their caregiver reported their estimated physical contacts at school; only 22.5 % had agreement within ±2 contacts between the observed and reported contacts. Fifty-eight percent of proxy-reported contacts were under-estimates.
Social contact rates observed among pupils at schools in rural Gambia were high, strongly age-assortative, and physical. Reporting of school contacts by proxies may underestimate the effect of school-age children in modelling studies of transmission of infections. New approaches are needed to quantify contacts within schools.
Households play an important role in the transmission of infectious diseases due to the close contact therein. Previous modeling studies on disease transmission with household-level mixing have explored the relationship between household size distribution and epidemic characteristics such as final epidemic sizes and the basic reproduction number but have not considered the epidemic impact of declining household sizes caused by demographic shifts. Here, we use a disease transmission model that incorporates demographic changes in household sizes to study the long-term transmission dynamics of measles in communities with varying household size distributions. We explore the impact of incorporating both household- and age-structured mixing on the dynamic properties of the transmission model and compare these dynamics across different household size distributions. Our analysis, based on the household- and age-structured model, shows that communities with larger household sizes require higher vaccination thresholds and bear a greater burden of infections. However, simulations show the apparent impact of changing household sizes is the combined result of changing birth rates and household mixing, and that changing birth rates likely play a larger role than changes in household mixing in shaping measles transmission dynamics (n.b, life-long immunity makes replenishment of population susceptibility from births a crucial transmission driver for measles). In addition, simulations of endemic transmission of measles within a hypothetical population formulated using aggregated world demographic data suggest the decline in household size (driven by changing fertility rates of the population), in addition to increasing vaccination coverage, could have had a significant impact on the incidence of measles over time.
Plasmodium vivax is the most geographically widespread malaria parasite. P. vivax has the ability to remain dormant (as a hypnozoite) in the human liver and subsequently reactivate, which makes control efforts more difficult. Given the majority of P. vivax infections are due to hypnozoite reactivation, targeting the hypnozoite reservoir with a radical cure is crucial for achieving P. vivax elimination. Stochastic effects can strongly influence dynamics when disease prevalence is low or when the population size is small. Hence, it is important to account for this when modelling malaria elimination. We use a stochastic multiscale model of P. vivax transmission to study the impacts of multiple rounds of mass drug administration (MDA) with a radical cure, accounting for superinfection and hypnozoite dynamics. Our results indicate multiple rounds of MDA with a high-efficacy drug are needed to achieve a substantial probability of elimination. This work has the potential to help guide P. vivax elimination strategies by quantifying elimination probabilities for an MDA approach.