Malaria has been a major driving force in the evolution of the human genome. In sub-Saharan African populations, two neighbouring polymorphisms in the Complement Receptor One (CR1) gene, named Sl2 and McCb, occur at high frequencies, consistent with selection by malaria. Previous studies have been inconclusive. Using a large case-control study of severe malaria in Kenyan children and statistical models adjusted for confounders, we estimate the relationship between Sl2 and McCb and malaria phenotypes, and find they have opposing associations. The Sl2 polymorphism is associated with markedly reduced odds of cerebral malaria and death, while the McCb polymorphism is associated with increased odds of cerebral malaria. We also identify an apparent interaction between Sl2 and α+thalassaemia, with the protective association of Sl2 greatest in children with normal α-globin. The complex relationship between these three mutations may explain previous conflicting findings, highlighting the importance of considering genetic interactions in disease-association studies.
MalariaGEN Consortial Project 1Application for access to data: https://www.malariagen.net/data/terms-use/human-gwas-data.
- Thomas Williams
- Thomas Williams
- J Alexandra Rowe
- D Herbert Opi
- D Herbert Opi
- Olivia Swann
- Dominic P Kwiatkowski
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: This work involved analysing blood samples from patients with malaria and from healthy controls. Written informed consent was obtained from the parents or legal guardians of all participants. The Kenyan studies received ethical approval from the Kenya Medical Research Institute National Ethical Review Committee (approval number SCC1192 for the case-control study and SCC3149 for the longitudinal cohort study), and the Malian studies received ethical approval from the University of Bamako and the University of Maryland (approval number #0899139), and were conducted in accordance with the Declaration of Helsinki.
- Madhukar Pai, McGill University, Canada
© 2018, Opi et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Fear over side-effects is one of the main drivers of COVID-19 vaccine hesitancy. A large literature in the behavioral and communication sciences finds that how risks are framed and presented to individuals affects their judgments of its severity. However, it remains unknown whether such framing changes can affect COVID-19 vaccine behavior and be deployed as policy solutions to reduce hesitancy.
We conducted a pre-registered randomized controlled trial among 8998 participants in the United States and the United Kingdom to examine the effects of different ways of framing and presenting vaccine side-effects on individuals’ willingness to get vaccinated and their perceptions of vaccine safety.
Adding a descriptive risk label (‘very low risk’) next to the numerical side-effect and providing a comparison to motor-vehicle mortality increased participants’ willingness to take the COVID-19 vaccine by 3.0 percentage points (p=0.003) and 2.4 percentage points (p=0.049), respectively. These effects were independent and additive and combining both framing strategies increased willingness to receive the vaccine by 6.1 percentage points (p<0.001). Mechanistically, we find evidence that these framing effects operate by increasing individuals’ perceptions of how safe the vaccine is.
Low-cost side-effect framing strategies can meaningfully affect vaccine intentions at a population level.
Heidelberg Institute of Global Health.
German Clinical Trials Registry (#DRKS00025551).
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron BA.1) by February 2022. We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 to February 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g. infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, that is, Beta, Delta, and Omicron BA.1. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.