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Article ; Online: Handling unpredictable ecosystems.

Niehus, Rene / Mitri, Sara

Nature ecology & evolution

2018 Volume 2, Issue 8, Page(s) 1207–1208

MeSH term(s)	Anti-Bacterial Agents ; Ecosystem
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2018-07-09
Publishing country	England
Document type	Journal Article ; Comment
ISSN	2397-334X
ISSN (online)	2397-334X
DOI	10.1038/s41559-018-0619-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Predicting subnational incidence of COVID-19 cases and deaths in EU countries.

Robert, Alexis / Chapman, Lloyd A C / Grah, Rok / Niehus, Rene / Sandmann, Frank / Prasse, Bastian / Funk, Sebastian / Kucharski, Adam J

BMC infectious diseases

2024 Volume 24, Issue 1, Page(s) 204

Abstract: Background: Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, ... ...

Abstract	Background: Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models. Methods: We used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given age-stratified data, and links reported case counts to routinely collected covariates (e.g. test number, vaccine coverage). We assessed the predictive performance of our model up to four weeks ahead using proper scoring rules and compared it to the European COVID-19 Forecast Hub ensemble model. Using simulations, we evaluated the impact of variations in transmission on the forecasts. We developed an open-source RShiny App to visualise the forecasts and scenarios. Results: At a national level, the median relative difference between our median weekly case forecasts and the data up to four weeks ahead was 25% (IQR: 12-50%) over the prediction period. The accuracy decreased as the forecast horizon increased (on average 24% increase in the median ranked probability score per added week), while the accuracy of death forecasts was more stable. Beyond two weeks, the model generated a narrow range of likely transmission dynamics. The median national case forecasts showed similar accuracy to forecasts from the European COVID-19 Forecast Hub ensemble model, but the prediction interval was narrower in our model. Generating forecasts under alternative transmission scenarios was therefore key to capturing the range of possible short-term transmission dynamics. Discussion: Our model captures changes in local COVID-19 outbreak dynamics, and enables quantification of short-term transmission risk at a subnational level. The outputs of the model improve our ability to identify areas where outbreaks are most likely, and are available to a wide range of public health professionals through the Shiny App we developed.
MeSH term(s)	Humans ; COVID-19/epidemiology ; Incidence ; Disease Outbreaks ; Public Health ; Forecasting
Language	English
Publishing date	2024-02-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-024-08986-x
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Article ; Online: Implications of reducing antibiotic treatment duration for antimicrobial resistance in hospital settings: A modelling study and meta-analysis.

Mo, Yin / Oonsivilai, Mathupanee / Lim, Cherry / Niehus, Rene / Cooper, Ben S

PLoS medicine

2023 Volume 20, Issue 6, Page(s) e1004013

Abstract: Background: Reducing antibiotic treatment duration is a key component of hospital antibiotic stewardship interventions. However, its effectiveness in reducing antimicrobial resistance is uncertain and a clear theoretical rationale for the approach is ... ...

Abstract	Background: Reducing antibiotic treatment duration is a key component of hospital antibiotic stewardship interventions. However, its effectiveness in reducing antimicrobial resistance is uncertain and a clear theoretical rationale for the approach is lacking. In this study, we sought to gain a mechanistic understanding of the relation between antibiotic treatment duration and the prevalence of colonisation with antibiotic-resistant bacteria in hospitalised patients. Methods and findings: We constructed 3 stochastic mechanistic models that considered both between- and within-host dynamics of susceptible and resistant gram-negative bacteria, to identify circumstances under which shortening antibiotic duration would lead to reduced resistance carriage. In addition, we performed a meta-analysis of antibiotic treatment duration trials, which monitored resistant gram-negative bacteria carriage as an outcome. We searched MEDLINE and EMBASE for randomised controlled trials published from 1 January 2000 to 4 October 2022, which allocated participants to varying durations of systemic antibiotic treatments. Quality assessment was performed using the Cochrane risk-of-bias tool for randomised trials. The meta-analysis was performed using logistic regression. Duration of antibiotic treatment and time from administration of antibiotics to surveillance culture were included as independent variables. Both the mathematical modelling and meta-analysis suggested modest reductions in resistance carriage could be achieved by reducing antibiotic treatment duration. The models showed that shortening duration is most effective at reducing resistance carriage in high compared to low transmission settings. For treated individuals, shortening duration is most effective when resistant bacteria grow rapidly under antibiotic selection pressure and decline rapidly when stopping treatment. Importantly, under circumstances whereby administered antibiotics can suppress colonising bacteria, shortening antibiotic treatment may increase the carriage of a particular resistance phenotype. We identified 206 randomised trials, which investigated antibiotic duration. Of these, 5 reported resistant gram-negative bacteria carriage as an outcome and were included in the meta-analysis. The meta-analysis determined that a single additional antibiotic treatment day is associated with a 7% absolute increase in risk of resistance carriage (80% credible interval 3% to 11%). Interpretation of these estimates is limited by the low number of antibiotic duration trials that monitored carriage of resistant gram-negative bacteria, as an outcome, contributing to a large credible interval. Conclusions: In this study, we found both theoretical and empirical evidence that reducing antibiotic treatment duration can reduce resistance carriage, though the mechanistic models also highlighted circumstances under which reducing treatment duration can, perversely, increase resistance. Future antibiotic duration trials should monitor antibiotic-resistant bacteria colonisation as an outcome to better inform antibiotic stewardship policies.
MeSH term(s)	Humans ; Anti-Bacterial Agents/adverse effects ; Duration of Therapy ; Drug Resistance, Bacterial
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2023-06-15
Publishing country	United States
Document type	Meta-Analysis ; Journal Article
ZDB-ID	2185925-5
ISSN	1549-1676 ; 1549-1277
ISSN (online)	1549-1676
ISSN	1549-1277
DOI	10.1371/journal.pmed.1004013
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Article ; Online: The evolution of strategy in bacterial warfare via the regulation of bacteriocins and antibiotics.

Niehus, Rene / Oliveira, Nuno M / Li, Aming / Fletcher, Alexander G / Foster, Kevin R

eLife

2021 Volume 10

Abstract: Bacteria inhibit and kill one another with a diverse array of compounds, including bacteriocins and antibiotics. These attacks are highly regulated, but we lack a clear understanding of the evolutionary logic underlying this regulation. Here, we combine ... ...

Abstract	Bacteria inhibit and kill one another with a diverse array of compounds, including bacteriocins and antibiotics. These attacks are highly regulated, but we lack a clear understanding of the evolutionary logic underlying this regulation. Here, we combine a detailed dynamic model of bacterial competition with evolutionary game theory to study the rules of bacterial warfare. We model a large range of possible combat strategies based upon the molecular biology of bacterial regulatory networks. Our model predicts that regulated strategies, which use quorum sensing or stress responses to regulate toxin production, will readily evolve as they outcompete constitutive toxin production. Amongst regulated strategies, we show that a particularly successful strategy is to upregulate toxin production in response to an incoming competitor's toxin, which can be achieved via stress responses that detect cell damage (competition sensing). Mirroring classical game theory, our work suggests a fundamental advantage to reciprocation. However, in contrast to classical results, we argue that reciprocation in bacteria serves not to promote peaceful outcomes but to enable efficient and effective attacks.
MeSH term(s)	Anti-Bacterial Agents/biosynthesis ; Bacterial Physiological Phenomena ; Bacteriocins/metabolism ; Biological Evolution ; Biological Warfare ; Quorum Sensing
Chemical Substances	Anti-Bacterial Agents ; Bacteriocins
Language	English
Publishing date	2021-09-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.69756
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Article: Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers.

Niehus, Rene / De Salazar, Pablo M / Taylor, Aimee R / Lipsitch, Marc

medRxiv : the preprint server for health sciences

2020

Abstract: Risk of COVID-19 infection in Wuhan has been estimated using imported case counts of international travelers, often under the assumption that all cases in travelers are ascertained. Recent work indicates variation among countries in detection capacity ... ...

Abstract	Risk of COVID-19 infection in Wuhan has been estimated using imported case counts of international travelers, often under the assumption that all cases in travelers are ascertained. Recent work indicates variation among countries in detection capacity for imported cases. Singapore has historically had very strong epidemiological surveillance and contact-tracing capacity and has shown in the COVID-19 epidemic evidence of a high sensitivity of case detection. We therefore used a Bayesian modeling approach to estimate the relative imported case detection capacity for other countries compared to that of Singapore. We estimate that the global ability to detect imported cases is 38% (95% HPDI 22% - 64%) of Singapore's capacity. Equivalently, an estimate of 2.8 (95% HPDI 1.5 - 4.4) times the current number of imported cases, could have been detected, if all countries had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, we found that the ability to detect imported cases relative to Singapore among high surveillance locations is 40% (95% HPDI 22% - 67%), among intermediate surveillance locations it is 37% (95% HPDI 18% - 68%), and among low surveillance locations it is 11% (95% HPDI 0% - 42%). Using a simple mathematical model, we further find that treating all travelers as if they were residents (rather than accounting for the brief stay of some of these travelers in Wuhan) can modestly contribute to underestimation of prevalence as well. We conclude that estimates of case counts in Wuhan based on assumptions of perfect detection in travelers may be underestimated by several fold, and severity correspondingly overestimated by several fold. Undetected cases are likely in countries around the world, with greater risk in countries of low detection capacity and high connectivity to the epicenter of the outbreak.
Keywords	covid19
Language	English
Publishing date	2020-02-18
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.02.13.20022707
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Article ; Online: Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.

Niehus, Rene / De Salazar, Pablo M / Taylor, Aimee R / Lipsitch, Marc

The Lancet. Infectious diseases

2020 Volume 20, Issue 7, Page(s) 803–808

Abstract: Background: The incidence of coronavirus disease 2019 (COVID-19) in Wuhan, China, has been estimated using imported case counts of international travellers, generally under the assumptions that all cases of the disease in travellers have been ... ...

Abstract	Background: The incidence of coronavirus disease 2019 (COVID-19) in Wuhan, China, has been estimated using imported case counts of international travellers, generally under the assumptions that all cases of the disease in travellers have been ascertained and that infection prevalence in travellers and residents is the same. However, findings indicate variation among locations in the capacity for detection of imported cases. Singapore has had very strong epidemiological surveillance and contact tracing capacity during previous infectious disease outbreaks and has consistently shown high sensitivity of case-detection during the COVID-19 outbreak. Methods: We used a Bayesian modelling approach to estimate the relative capacity for detection of imported cases of COVID-19 for 194 locations (excluding China) compared with that for Singapore. We also built a simple mathematical model of the point prevalence of infection in visitors to an epicentre relative to that in residents. Findings: The weighted global ability to detect Wuhan-to-location imported cases of COVID-19 was estimated to be 38% (95% highest posterior density interval [HPDI] 22-64) of Singapore's capacity. This value is equivalent to 2·8 (95% HPDI 1·5-4·4) times the current number of imported and reported cases that could have been detected if all locations had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, the ability to detect imported cases relative to Singapore was 40% (95% HPDI 22-67) among locations with high surveillance capacity, 37% (18-68) among locations with medium surveillance capacity, and 11% (0-42) among locations with low surveillance capacity. Treating all travellers as if they were residents (rather than accounting for the brief stay of some of these travellers in Wuhan) contributed modestly to underestimation of prevalence. Interpretation: Estimates of case counts in Wuhan based on assumptions of 100% detection in travellers could have been underestimated by several fold. Furthermore, severity estimates will be inflated several fold since they also rely on case count estimates. Finally, our model supports evidence that underdetected cases of COVID-19 have probably spread in most locations around the world, with greatest risk in locations of low detection capacity and high connectivity to the epicentre of the outbreak. Funding: US National Institute of General Medical Sciences, and Fellowship Foundation Ramon Areces.
MeSH term(s)	Bayes Theorem ; Betacoronavirus ; Bias ; COVID-19 ; China/epidemiology ; Coronavirus Infections/epidemiology ; Coronavirus Infections/transmission ; Data Interpretation, Statistical ; Humans ; Pandemics ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/transmission ; Population Surveillance/methods ; Prevalence ; SARS-CoV-2 ; Singapore/epidemiology ; Travel
Keywords	covid19
Language	English
Publishing date	2020-04-01
Publishing country	United States
Document type	Journal Article ; Observational Study ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2061641-7
ISSN	1474-4457 ; 1473-3099
ISSN (online)	1474-4457
ISSN	1473-3099
DOI	10.1016/S1473-3099(20)30229-2
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Article ; Online: Identifying Locations with Possible Undetected Imported Severe Acute Respiratory Syndrome Coronavirus 2 Cases by Using Importation Predictions.

De Salazar, Pablo Martinez / Niehus, René / Taylor, Aimee / Buckee, Caroline O'Flaherty / Lipsitch, Marc

Emerging infectious diseases

2020 Volume 26, Issue 7, Page(s) 1465–1469

Abstract: Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exported from mainland China could lead to self-sustained outbreaks in other countries. By February 2020, several countries were reporting imported SARS-CoV-2 cases. To ... ...

Abstract	Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exported from mainland China could lead to self-sustained outbreaks in other countries. By February 2020, several countries were reporting imported SARS-CoV-2 cases. To contain the virus, early detection of imported SARS-CoV-2 cases is critical. We used air travel volume estimates from Wuhan, China, to international destinations and a generalized linear regression model to identify locations that could have undetected imported cases. Our model can be adjusted to account for exportation of cases from other locations as the virus spreads and more information on importations and transmission becomes available. Early detection and appropriate control measures can reduce the risk for transmission in all locations.
MeSH term(s)	Betacoronavirus ; COVID-19 ; China/epidemiology ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Coronavirus Infections/transmission ; Humans ; Linear Models ; Pandemics/prevention & control ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/transmission ; SARS-CoV-2 ; Travel
Keywords	covid19
Language	English
Publishing date	2020-06-21
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1380686-5
ISSN	1080-6059 ; 1080-6040
ISSN (online)	1080-6059
ISSN	1080-6040
DOI	10.3201/eid2607.200250
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Article ; Online: The influence of COVID-19 risk perception and vaccination status on the number of social contacts across Europe: insights from the CoMix study.

Wambua, James / Loedy, Neilshan / Jarvis, Christopher I / Wong, Kerry L M / Faes, Christel / Grah, Rok / Prasse, Bastian / Sandmann, Frank / Niehus, Rene / Johnson, Helen / Edmunds, W John / Beutels, Philippe / Hens, Niel / Coletti, Pietro

BMC public health

2023 Volume 23, Issue 1, Page(s) 1350

Abstract: Background: The SARS-CoV-2 transmission dynamics have been greatly modulated by human contact behaviour. To curb the spread of the virus, global efforts focused on implementing both Non-Pharmaceutical Interventions (NPIs) and pharmaceutical ... ...

Abstract	Background: The SARS-CoV-2 transmission dynamics have been greatly modulated by human contact behaviour. To curb the spread of the virus, global efforts focused on implementing both Non-Pharmaceutical Interventions (NPIs) and pharmaceutical interventions such as vaccination. This study was conducted to explore the influence of COVID-19 vaccination status and risk perceptions related to SARS-CoV-2 on the number of social contacts of individuals in 16 European countries. Methods: We used data from longitudinal surveys conducted in the 16 European countries to measure social contact behaviour in the course of the pandemic. The data consisted of representative panels of participants in terms of gender, age and region of residence in each country. The surveys were conducted in several rounds between December 2020 and September 2021 and comprised of 29,292 participants providing a total of 111,103 completed surveys. We employed a multilevel generalized linear mixed effects model to explore the influence of risk perceptions and COVID-19 vaccination status on the number of social contacts of individuals. Results: The results indicated that perceived severity played a significant role in social contact behaviour during the pandemic after controlling for other variables (p-value < 0.001). More specifically, participants who had low or neutral levels of perceived severity reported 1.25 (95% Confidence intervals (CI) 1.13 - 1.37) and 1.10 (95% CI 1.00 - 1.21) times more contacts compared to those who perceived COVID-19 to be a serious illness, respectively. Additionally, vaccination status was also a significant predictor of contacts (p-value < 0.001), with vaccinated individuals reporting 1.31 (95% CI 1.23 - 1.39) times higher number of contacts than the non-vaccinated. Furthermore, individual-level factors played a more substantial role in influencing contact behaviour than country-level factors. Conclusion: Our multi-country study yields significant insights on the importance of risk perceptions and vaccination in behavioral changes during a pandemic emergency. The apparent increase in social contact behaviour following vaccination would require urgent intervention in the event of emergence of an immune escaping variant.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; SARS-CoV-2 ; COVID-19 Vaccines ; Vaccination ; Perception
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2023-07-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041338-5
ISSN	1471-2458 ; 1471-2458
ISSN (online)	1471-2458
ISSN	1471-2458
DOI	10.1186/s12889-023-16252-z
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Article ; Online: Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China

Niehus, Rene / De Salazar, Pablo M / Taylor, Aimee R / Lipsitch, Marc

The Lancet Infectious Diseases

2020 Volume 20, Issue 7, Page(s) 803–808

Keywords	Infectious Diseases ; covid19
Language	English
Publisher	Elsevier BV
Publishing country	us
Document type	Article ; Online
ZDB-ID	2061641-7
ISSN	1474-4457 ; 1473-3099
ISSN (online)	1474-4457
ISSN	1473-3099
DOI	10.1016/s1473-3099(20)30229-2
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers

Rene Niehus / Pablo M De Salazar / Aimee Taylor / Marc Lipsitch

Abstract	Risk of COVID-19 infection in Wuhan has been estimated using imported case counts of international travelers, often under the assumption that all cases in travelers are ascertained. Recent work indicates variation among countries in detection capacity for imported cases. Singapore has historically had very strong epidemiological surveillance and contact-tracing capacity and has shown in the COVID-19 epidemic evidence of a high sensitivity of case detection. We therefore used a Bayesian modeling approach to estimate the relative imported case detection capacity for other countries compared to that of Singapore. We estimate that the global ability to detect imported cases is 38% (95% HPDI 22% - 64%) of Singapore′s capacity. Equivalently, an estimate of 2.8 (95% HPDI 1.5 - 4.4) times the current number of imported cases, could have been detected, if all countries had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, we found that the ability to detect imported cases relative to Singapore among high surveillance locations is 40% (95% HPDI 22% - 67%), among intermediate surveillance locations it is 37% (95% HPDI 18% - 68%), and among low surveillance locations it is 11% (95% HPDI 0% - 42%). Using a simple mathematical model, we further find that treating all travelers as if they were residents (rather than accounting for the brief stay of some of these travelers in Wuhan) can modestly contribute to underestimation of prevalence as well. We conclude that estimates of case counts in Wuhan based on assumptions of perfect detection in travelers may be underestimated by several fold, and severity correspondingly overestimated by several fold. Undetected cases are likely in countries around the world, with greater risk in countries of low detection capacity and high connectivity to the epicenter of the outbreak.
Keywords	covid19
Publisher	medrxiv
Document type	Article ; Online
DOI	10.1101/2020.02.13.20022707
Database	COVID19

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