Epidemiology

Antibiotic-resistance plasmid amplified among MRSA cases in an urban jail and its connected communities

1. Stephanie N. Thiede
2. Hannah Steinberg
3. Emily Benedict
4. Sarah Sansom
5. Alla Aroutcheva
6. Kyle J. Gontjes
7. Katherine Winner
8. Sonya Royzenblat
9. Ali Pirani
10. Robert A Weinstein
11. Chad Zawitz
12. Nicholas M. Moore
13. Kyle J. Popovich
14. Evan S. Snitkin

Reviewed by PREreview

Spatiotemporal relationships between extreme weather events and arbovirus transmission across Brazil

1. Victoria M Cox
2. Felipe Campos de Melo Iani
3. Wes Hinsley
4. Pedro S Peixoto
5. Flavio Codeço Coelho
6. Carlos Augusto Prete
7. Megan O’Driscoll
8. Neil Ferguson
9. Samir Bhatt
10. Nuno R Faria
11. Ilaria Dorigatti

• Curated by eLife

  eLife Assessment

  This study presents valuable findings from a spatiotemporal analysis of arbovirus case notification data from 2013 to 2020 in Brazil, reporting associations between covariates representing potential drivers of arbovirus transmission and recorded incidence. The work is methodologically solid, though it is unclear how much explanatory power inclusion of the covariates adds. The findings will be of interest to researchers working on the epidemiology of arboviruses.

Reviewed by eLife

A natural experiment in Kenya reveals durable immunosuppressive effects of early childhood malaria: a longitudinal cohort study

1. Mercy S Safari
2. Timothy O Makori
3. Elijah T Gicheru
4. Maureen W Mburu
5. Omar Nyawa
6. Faiz Shee
7. James Nyagwange
8. Eunice W Kagucia
9. Francis Ndungu
10. Timothy Chege
11. James O Tuju
12. Charles J Sande

• Curated by eLife

  eLife Assessment

  This important study sought to investigate the role that early childhood malaria exposure plays in the development of antibody responses to unrelated pathogens and vaccine-derived antigens in Kenyan children. In this natural experiment, the authors compare antibody levels among children who have been exposed to different levels of malaria transmission by using protein microarray technology. Although the findings are of importance, the evidence remains incomplete, and the analysis would benefit from a more in-depth evaluation of potential confounders. With the appropriate analysis, the findings will be of great interest for global health, immunology, and vaccine development.

Reviewed by eLife

Refining uncertainty about the TAK-003 dengue vaccine with a multi-level model of clinical efficacy trial data

1. Manar Alkuzweny
2. Guido España
3. T Alex Perkins

• Curated by eLife

  eLife Assessment

  This paper presents important new findings about the impact of the TAK-003 vaccine against dengue based on a convincing reanalysis of trial data. The results corroborate those of the original trial analyses, but with reduced uncertainty about the estimates of the impact of the vaccine. The findings will be of interest to clinicians, infectious disease epidemiologists, trial statisticians and policymakers seeking to understand the vaccine's efficacy profile and associated uncertainties.

Reviewed by eLife

Using step selection functions to analyse human mobility using telemetry data in infectious disease epidemiology: a case study of leptospirosis

1. Pablo Ruiz Cuenca
2. Fabio Neves Souza
3. Roberta Coutinho do Nascimento
4. Ariane Goncalves da Silva
5. Max T Eyre
6. Juliet O Santana
7. Daiana Santos de Oliveira
8. Emile Victoria Ribeiro de Souza
9. Fabiana Almerinda G Palma
10. Diogo César de Carvalho Santiago
11. Priscyla dos Santos Ribeiro
12. Priscilla Elizabeth Ferreira dos Santos
13. Hussein Khalil
14. Jonathan M Read
15. Cleber Cremonese
16. Federico Costa
17. Emanuele Giorgi

• Curated by eLife

  eLife Assessment

  This study makes a novel and valuable contribution by adapting step selection functions, traditionally used in animal ecology, to explore human movement and environmental risk exposure in urban slums, offering a promising framework for spatial epidemiology, particularly regarding leptospirosis. The integration of GPS telemetry with environmental data and the stratification by gender and serostatus are notable strengths that enhance the study's relevance for public health applications. The strength of evidence is compelling.

Reviewed by eLife

Reassessing the link between adiposity and head and neck cancer: a Mendelian randomization study

1. Fernanda Morales Berstein
2. Jasmine Khouja
3. Mark Gormley
4. Elmira Ebrahimi
5. Shama Virani
6. James D McKay
7. Paul Brennan
8. Tom G Richardson
9. Caroline L Relton
10. George Davey Smith
11. M Carolina Borges
12. Tom Dudding
13. Rebecca C Richmond

• Curated by eLife

  eLife Assessment

  This important study reports that higher genetically predicted BMI is associated with a modestly increased risk of head and neck cancer. The convincing evidence is supported by rigorous Mendelian Randomization approaches, using multiple genetic instruments and models that reduce sensitivity to pleiotropy. However, results from pleiotropy-robust analyses were less consistent, which limits the strength of causal inference. The work will be of interest to researchers studying cancer risk factors and genetic epidemiology.

Reviewed by eLife

Inferring variant-specific effective reproduction numbers from combined case and sequencing data

1. Marlin D Figgins
2. Trevor Bedford

• Curated by eLife

  eLife Assessment

  This study provides new important insights concerning pathogen variant-specific reproduction parameters from molecular sequencing and case finding. The methods for inferring which variants will likely emerge in subsequent epidemic cycles are solid. This article is of broad interest to infectious disease epidemiology researchers and mathematical modellers of the COVID-19 pandemic.

Reviewed by eLife, ScreenIT

Heterogenous associations of polygenic indices of 35 traits with mortality

1. Hannu Lahtinen
2. Jaakko Kaprio
3. Andrea Ganna
4. Kaarina Korhonen
5. Stefano Lombardi
6. Karri Silventoinen
7. Pekka Martikainen

• Curated by eLife

  eLife Assessment

  This valuable study reports convincing evidence about associations between 35 polygenic indices (PGIs) for social, behavioral, and psychological traits, along with some non-fatal health conditions (e.g., BMI) and all-cause mortality in data from Finnish population-based surveys and a twin cohort linked with administrative registers. PGIs for education, depression, alcohol use, smoking, BMI, and self-rated health showed the strongest associations with all-cause mortality, on the order of ~10% increment in risk per PGI standard deviation. Effect sizes from twin-difference analyses tended to be slightly larger than the effect sizes from population cohorts, opposite the pattern generally observed when testing PGI associations with their target phenotypes and supporting robustness of findings to confounding by population stratification.

Reviewed by eLife

Forecasting the spatial spread of an Ebola epidemic in real time: Comparing predictions of mathematical models and experts

1. James D Munday
2. Alicia Rosello
3. W John Edmunds
4. Sebastian Funk

• Curated by eLife

  eLife Assessment

  This manuscript provides valuable evidence comparing the performance of mathematical models and opinions from experts engaged in outbreak response in forecasting the spatial spread of an Ebola epidemic. The evidence supporting the conclusions is convincing. It will be of interest to disease modellers, infectious disease epidemiologists, policy-makers, and those who need to inform policy-makers during an outbreak.

Reviewed by eLife

Estimating probabilities of malaria importation in southern Mozambique through P. falciparum genomics and mobility patterns

1. Arnau Pujol
2. Arlindo Chidimatembue
3. Clemente da Silva
4. Simone Boene
5. Henriques Mbeve
6. Pau Cisteró
7. Carla García-Fernández
8. Arnau Vañó-Boira
9. Dário Tembisse
10. José Inácio
11. Glória Matambisso
12. Fabião Luis
13. Nelo Ndimande
14. Humberto Munguambe
15. Lidia Nhamussua
16. Wilson Simone
17. Andrés Aranda-Díaz
18. Manuel García-Ulloa
19. Neide Canana
20. Maria Tusell
21. Júlia Montaña
22. Laura Fuente-Soro
23. Khalid Ussene Bapu
24. Maxwell Murphy
25. Bernardete Rafael
26. Eduard Rovira-Vallbona
27. Caterina Guinovart
28. Bryan Greenhouse
29. Sonia Maria Enosse
30. Francisco Saúte
31. Pedro Aide
32. Baltazar Candrinho
33. Alfredo Mayor

• Curated by eLife

  eLife Assessment

  This study introduces a useful method to estimate the probability that a malaria case is imported and to identify the geographic origin of parasites by using a Bayesian approach that integrates epidemiological, travel, and genetic data. The authors provide convincing evidence that the approach can reliably identify the main sources of malaria imports. This work will be of great interest to the area of genomic epidemiology and public health strategies aiming to eliminate malaria.

Reviewed by eLife