ArticleBiology letters2020
Early warning signals of malaria resurgence in Kericho, Kenya.
Article in Biology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Multivariate resilience indicators to anticipate vector-borne disease outbreaks: A West Nile virus case-study.PLoS computational biology · 2025Article
- Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.PLoS computational biology · 2025Article
- Early warning signals do not predict a warming-induced experimental epidemic.PLOS global public health · 2025Article
- Advancing Early Warning Systems for Malaria: Progress, challenges, and future directions - A scoping review.PLOS global public health · 2025Article
- Monitoring resilience in bursts.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Influence of environmental, geographic, socio-demographic, and epidemiological factors on presence of malaria at the community level in two continents.Scientific reports · 2024Article
- Anticipating regime shifts by mixing early warning signals from different nodes.Nature communications · 2024Article
- Early warning signals have limited applicability to empirical lake data.Nature communications · 2023Article
- Space-time modelling of monthly malaria incidence for seasonal associated drivers and early epidemic detection in Southern Ethiopia.Malaria journal · 2023Article
- Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.The Science of the total environment · 2023Article
- The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide.PLOS global public health · 2023Article
- Anticipating infectious disease re-emergence and elimination: a test of early warning signals using empirically based models.Journal of the Royal Society, Interface · 2022Article
- Performance of early warning signals for disease re-emergence: A case study on COVID-19 data.PLoS computational biology · 2022Article
- Overlapping timescales obscure early warning signals of the second COVID-19 wave.Proceedings. Biological sciences · 2022Article
- Early warning signal reliability varies with COVID-19 waves.Biology letters · 2021Article
- Early warning signals of infectious disease transitions: a review.Journal of the Royal Society, Interface · 2021Review
- A vulnerability index for COVID-19: spatial analysis at the subnational level in Kenya.BMJ global health · 2020Article
- Anticipating the Novel Coronavirus Disease (COVID-19) Pandemic.Frontiers in public health · 2020Article
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Authors and funding
3 authors.
Funding
Abstract
Campaigns to eliminate infectious diseases could be greatly aided by methods for providing early warning signals of resurgence. Theory predicts that as a disease transmission system undergoes a transition from stability at the disease-free equilibrium to sustained transmission, it will exhibit characteristic behaviours known as critical slowing down, referring to the speed at which fluctuations in the number of cases are dampened, for instance the extinction of a local transmission chain after infection from an imported case. These phenomena include increases in several summary statistics, including lag-1 autocorrelation, variance and the first difference of variance. Here, we report the first empirical test of this prediction during the resurgence of malaria in Kericho, Kenya. For 10 summary statistics, we measured the approach to criticality in a rolling window to quantify the size of effect and directions. Nine of the statistics increased as predicted and variance, the first difference of variance, autocovariance, lag-1 autocorrelation and decay time returned early warning signals of critical slowing down based on permutation tests. These results show that time series of disease incidence collected through ordinary surveillance activities may exhibit characteristic signatures prior to an outbreak, a phenomenon that may be quite general among infectious disease systems.
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