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Article ; Online: Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics.

Routledge, Isobel / Unwin, H Juliette T / Bhatt, Samir

2021 Volume 11, Issue 1, Page(s) 14495

Abstract: Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer ... ...

Abstract	Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, genetic distance or accessibility matrices) with temporal information into a single inference framework to infer malaria reproduction numbers. Twelve scenarios were defined, representing different assumptions about the likelihood of transmission occurring over different geographic distances and likelihood of missing infections (as well as high and low amounts of uncertainty in this estimate). These scenarios were applied to four individual level datasets from malaria eliminating contexts to estimate individual reproduction numbers and how they varied over space and time. Model comparison suggested that including spatial information improved models as measured by second order AIC (ΔAICc), compared to time only results. Across scenarios and across datasets, including spatial information tended to increase the seasonality of temporal patterns in reproduction numbers and reduced noise in the temporal distribution of reproduction numbers. The best performing parameterisations assumed long-range transmission (> 200 km) was possible. Our approach is flexible and provides the potential to incorporate other sources of information which can be converted into distance or adjacency matrices such as travel times or molecular markers.
MeSH term(s)	Basic Reproduction Number ; China/epidemiology ; El Salvador/epidemiology ; Eswatini/epidemiology ; Humans ; Malaria/epidemiology ; Malaria/transmission ; Malaria, Falciparum/epidemiology ; Malaria, Falciparum/transmission ; Malaria, Vivax/epidemiology ; Malaria, Vivax/transmission ; Travel
Language	English
Publishing date	2021-07-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-93238-0
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Article ; Online: Quantifying the direct and indirect protection provided by insecticide treated bed nets against malaria.

Unwin, H Juliette T / Sherrard-Smith, Ellie / Churcher, Thomas S / Ghani, Azra C

Nature communications

2023 Volume 14, Issue 1, Page(s) 676

Abstract: Long lasting insecticidal nets (LLINs) provide both direct and indirect protection against malaria. As pyrethroid resistance evolves in mosquito vectors, it will be useful to understand how the specific benefits LLINs afford individuals and communities ... ...

Abstract	Long lasting insecticidal nets (LLINs) provide both direct and indirect protection against malaria. As pyrethroid resistance evolves in mosquito vectors, it will be useful to understand how the specific benefits LLINs afford individuals and communities may be affected. Here we use modelling to show that there is no minimum LLIN usage needed for users and non-users to benefit from community protection. Modelling results also indicate that pyrethroid resistance in local mosquitoes will likely diminish the direct and indirect benefits from insecticides, leaving the barrier effects intact, but LLINs are still expected to provide enhanced benefit over untreated nets even at high levels of pyrethroid resistance.
MeSH term(s)	Animals ; Humans ; Pyrethrins ; Mosquito Control/methods ; Insecticide Resistance ; Insecticide-Treated Bednets ; Anopheles ; Insecticides/pharmacology ; Malaria/prevention & control
Chemical Substances	Pyrethrins ; Insecticides
Language	English
Publishing date	2023-02-08
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-36356-9
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Article ; Online: List child dependents on death certificates.

Flaxman, Seth / Kasonka, Lackson / Cluver, Lucie / Souza, Andrea Santos / Nelson, Charles A / Blenkinsop, Alexandra / Unwin, H Juliette T / Hillis, Susan

Science (New York, N.Y.)

2023 Volume 380, Issue 6644, Page(s) 467

MeSH term(s)	Child ; Humans ; Child, Orphaned ; COVID-19/mortality ; Death Certificates ; Models, Statistical ; Cause of Death
Language	English
Publishing date	2023-05-04
Publishing country	United States
Document type	Letter
ZDB-ID	128410-1
ISSN	1095-9203 ; 0036-8075
ISSN (online)	1095-9203
ISSN	0036-8075
DOI	10.1126/science.adh8784
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Book ; Online: A comparison of short-term probabilistic forecasts for the incidence of COVID-19 using mechanistic and statistical time series models

Banholzer, Nicolas / Mellan, Thomas / Unwin, H Juliette T / Feuerriegel, Stefan / Mishra, Swapnil / Bhatt, Samir

2023

Abstract: Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative performance remain. ...

Abstract	Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative performance remain. Here, we compare short-term probabilistic forecasts of popular mechanistic models based on the renewal equation with forecasts of statistical time series models. Our empirical comparison is based on data of the daily incidence of COVID-19 across six large US states over the first pandemic year. We find that, on average, probabilistic forecasts from statistical time series models are overall at least as accurate as forecasts from mechanistic models. Moreover, statistical time series models better capture volatility. Our findings suggest that domain knowledge, which is integrated into mechanistic models by making assumptions about disease dynamics, does not improve short-term forecasts of disease incidence. We note, however, that forecasting is often only one of many objectives and thus mechanistic models remain important, for example, to model the impact of vaccines or the emergence of new variants. Comment: 37 pages, 4 Figures, 9 Appendix figures
Keywords	Statistics - Applications ; Computer Science - Machine Learning ; Quantitative Biology - Populations and Evolution ; Statistics - Machine Learning
Publishing date	2023-05-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Deep learning and MCMC with aggVAE for shifting administrative boundaries

Semenova, Elizaveta / Mishra, Swapnil / Bhatt, Samir / Flaxman, Seth / Unwin, H Juliette T

mapping malaria prevalence in Kenya

2023

Abstract: Model-based disease mapping remains a fundamental policy-informing tool in the fields of public health and disease surveillance. Hierarchical Bayesian models have emerged as the state-of-the-art approach for disease mapping since they are able to both ... ...

Abstract	Model-based disease mapping remains a fundamental policy-informing tool in the fields of public health and disease surveillance. Hierarchical Bayesian models have emerged as the state-of-the-art approach for disease mapping since they are able to both capture structure in the data and robustly characterise uncertainty. When working with areal data, e.g.~aggregates at the administrative unit level such as district or province, current models rely on the adjacency structure of areal units to account for spatial correlations and perform shrinkage. The goal of disease surveillance systems is to track disease outcomes over time. This task is especially challenging in crisis situations which often lead to redrawn administrative boundaries, meaning that data collected before and after the crisis are no longer directly comparable. Moreover, the adjacency-based approach ignores the continuous nature of spatial processes and cannot solve the change-of-support problem, i.e.~when estimates are required to be produced at different administrative levels or levels of aggregation. We present a novel, practical, and easy to implement solution to solve these problems relying on a methodology combining deep generative modelling and fully Bayesian inference: we build on the recently proposed PriorVAE method able to encode spatial priors over small areas with variational autoencoders by encoding aggregates over administrative units. We map malaria prevalence in Kenya, a country in which administrative boundaries changed in 2010.
Keywords	Computer Science - Machine Learning ; Statistics - Machine Learning
Subject code	006
Publishing date	2023-05-31
Publishing country	us
Document type	Book ; Online
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Article ; Online: Analysis of the potential for a malaria vaccine to reduce gaps in malaria intervention coverage.

Unwin, H Juliette T / Mwandigha, Lazaro / Winskill, Peter / Ghani, Azra C / Hogan, Alexandra B

Malaria journal

2021 Volume 20, Issue 1, Page(s) 438

Abstract: Background: The RTS,S/AS01 malaria vaccine is currently being evaluated in a cluster-randomized pilot implementation programme in three African countries. This study seeks to identify whether vaccination could reach additional children who are at risk ... ...

Abstract	Background: The RTS,S/AS01 malaria vaccine is currently being evaluated in a cluster-randomized pilot implementation programme in three African countries. This study seeks to identify whether vaccination could reach additional children who are at risk from malaria but do not currently have access to, or use, core malaria interventions. Methods: Using data from household surveys, the overlap between malaria intervention coverage and childhood vaccination (diphtheria-tetanus-pertussis dose 3, DTP3) uptake in 20 African countries with at least one first administrative level unit with Plasmodium falciparum parasite prevalence greater than 10% was calculated. Multilevel logistic regression was used to explore patterns of overlap by demographic and socioeconomic variables. The public health impact of delivering RTS,S/AS01 to those children who do not use an insecticide-treated net (ITN), but who received the DTP3 vaccine, was also estimated. Results: Uptake of DTP3 was higher than malaria intervention coverage in most countries. Overall, 34% of children did not use ITNs and received DTP3, while 35% of children used ITNs and received DTP3, although this breakdown varied by country. It was estimated that there are 33 million children in these 20 countries who do not use an ITN. Of these, 23 million (70%) received the DTP3 vaccine. Vaccinating those 23 million children who receive DTP3 but do not use an ITN could avert up to an estimated 9.7 million (range 8.5-10.8 million) clinical malaria cases each year, assuming all children who receive DTP3 are administered all four RTS,S doses. An additional 10.8 million (9.5-12.0 million) cases could be averted by vaccinating those 24 million children who receive the DTP3 vaccine and use an ITN. Children who had access to or used an ITN were 9-13% more likely to reside in rural areas compared to those who had neither intervention regardless of vaccination status. Mothers' education status was a strong predictor of intervention uptake and was positively associated with use of ITNs and vaccination uptake and negatively associated with having access to an ITN but not using it. Wealth was also a strong predictor of intervention coverage. Conclusions: Childhood vaccination to prevent malaria has the potential to reduce inequity in access to existing malaria interventions and could substantially reduce the childhood malaria burden in sub-Saharan Africa, even in regions with lower existing DTP3 coverage.
MeSH term(s)	Africa South of the Sahara ; Child, Preschool ; Educational Status ; Female ; Humans ; Infant ; Insecticide-Treated Bednets/statistics & numerical data ; Malaria/prevention & control ; Malaria Vaccines/administration & dosage ; Male ; Odds Ratio ; Prospective Studies ; Rural Population ; Social Class ; Urban Population
Chemical Substances	Malaria Vaccines
Language	English
Publishing date	2021-11-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2091229-8
ISSN	1475-2875 ; 1475-2875
ISSN (online)	1475-2875
ISSN	1475-2875
DOI	10.1186/s12936-021-03966-x
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Article ; Online: Estimating the Effect of Social Distancing Interventions on COVID-19 in the United States.

Olney, Andrew M / Smith, Jesse / Sen, Saunak / Thomas, Fridtjof / Unwin, H Juliette T

American journal of epidemiology

2021 Volume 190, Issue 8, Page(s) 1504–1509

Abstract: Since its global emergence in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. When medical treatments for the virus were still emerging and a vaccine was not yet available, state and ... ...

Abstract	Since its global emergence in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. When medical treatments for the virus were still emerging and a vaccine was not yet available, state and local governments sought to limit its spread by enacting various social-distancing interventions, such as school closures and lockdowns; however, the effectiveness of these interventions was unknown. We applied an established, semimechanistic Bayesian hierarchical model of these interventions to the spread of SARS-CoV-2 from Europe to the United States, using case fatalities from February 29, 2020, up to April 25, 2020, when some states began reversing their interventions. We estimated the effects of interventions across all states, contrasted the estimated reproduction numbers before and after lockdown for each state, and contrasted the predicted number of future fatalities with the actual number of fatalities as a check of the model's validity. Overall, school closures and lockdowns were the only interventions modeled that had a reliable impact on the time-varying reproduction number, and lockdown appears to have played a key role in reducing that number to below 1.0. We conclude that reversal of lockdown without implementation of additional, equally effective interventions will enable continued, sustained transmission of SARS-CoV-2 in the United States.
MeSH term(s)	Basic Reproduction Number ; Bayes Theorem ; COVID-19/epidemiology ; COVID-19/prevention & control ; Communicable Disease Control/methods ; Communicable Disease Control/statistics & numerical data ; Europe/epidemiology ; Humans ; Physical Distancing ; Quarantine/statistics & numerical data ; SARS-CoV-2 ; United States/epidemiology
Language	English
Publishing date	2021-01-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2937-3
ISSN	1476-6256 ; 0002-9262
ISSN (online)	1476-6256
ISSN	0002-9262
DOI	10.1093/aje/kwaa293
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Article ; Online: COVID-19 in Japan, January-March 2020: insights from the first three months of the epidemic.

Imai, Natsuko / Gaythorpe, Katy A M / Bhatia, Sangeeta / Mangal, Tara D / Cuomo-Dannenburg, Gina / Unwin, H Juliette T / Jauneikaite, Elita / Ferguson, Neil M

BMC infectious diseases

2022 Volume 22, Issue 1, Page(s) 493

Abstract: Background: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. ... ...

Abstract	Background: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. Methods: We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, R Results: The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with R Conclusions: Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.
MeSH term(s)	Adult ; Bayes Theorem ; COVID-19/epidemiology ; Humans ; Japan/epidemiology ; Pandemics/prevention & control ; SARS-CoV-2 ; Young Adult
Language	English
Publishing date	2022-05-25
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/s12879-022-07469-1
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Article ; Online: Orphanhood and Caregiver Loss Among Children Based on New Global Excess COVID-19 Death Estimates.

Hillis, Susan / N'konzi, Joel-Pascal Ntwali / Msemburi, William / Cluver, Lucie / Villaveces, Andrés / Flaxman, Seth / Unwin, H Juliette T

JAMA pediatrics

2022 Volume 176, Issue 11, Page(s) 1145–1148

MeSH term(s)	Child ; Humans ; Caregivers ; COVID-19 ; Acquired Immunodeficiency Syndrome ; Foster Home Care
Language	English
Publishing date	2022-11-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2701223-2
ISSN	2168-6211 ; 2168-6203
ISSN (online)	2168-6211
ISSN	2168-6203
DOI	10.1001/jamapediatrics.2022.3157
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Article ; Online: Assessment of COVID-19 as the Underlying Cause of Death Among Children and Young People Aged 0 to 19 Years in the US.

Flaxman, Seth / Whittaker, Charles / Semenova, Elizaveta / Rashid, Theo / Parks, Robbie M / Blenkinsop, Alexandra / Unwin, H Juliette T / Mishra, Swapnil / Bhatt, Samir / Gurdasani, Deepti / Ratmann, Oliver

JAMA network open

2023 Volume 6, Issue 1, Page(s) e2253590

Abstract: Importance: COVID-19 was the underlying cause of death for more than 940 000 individuals in the US, including at least 1289 children and young people (CYP) aged 0 to 19 years, with at least 821 CYP deaths occurring in the 1-year period from August 1, ... ...

Abstract	Importance: COVID-19 was the underlying cause of death for more than 940 000 individuals in the US, including at least 1289 children and young people (CYP) aged 0 to 19 years, with at least 821 CYP deaths occurring in the 1-year period from August 1, 2021, to July 31, 2022. Because deaths among US CYP are rare, the mortality burden of COVID-19 in CYP is best understood in the context of all other causes of CYP death. Objective: To determine whether COVID-19 is a leading (top 10) cause of death in CYP in the US. Design, setting, and participants: This national population-level cross-sectional epidemiological analysis for the years 2019 to 2022 used data from the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database on underlying cause of death in the US to identify the ranking of COVID-19 relative to other causes of death among individuals aged 0 to 19 years. COVID-19 deaths were considered in 12-month periods between April 1, 2020, and August 31, 2022, compared with deaths from leading non-COVID-19 causes in 2019, 2020, and 2021. Main outcomes and measures: Cause of death rankings by total number of deaths, crude rates per 100 000 population, and percentage of all causes of death, using the National Center for Health Statistics 113 Selected Causes of Death, for ages 0 to 19 and by age groupings (<1 year, 1-4 years, 5-9 years, 10-14 years, 15-19 years). Results: There were 821 COVID-19 deaths among individuals aged 0 to 19 years during the study period, resulting in a crude death rate of 1.0 per 100 000 population overall; 4.3 per 100 000 for those younger than 1 year; 0.6 per 100 000 for those aged 1 to 4 years; 0.4 per 100 000 for those aged 5 to 9 years; 0.5 per 100 000 for those aged 10 to 14 years; and 1.8 per 100 000 for those aged 15 to 19 years. COVID-19 mortality in the time period of August 1, 2021, to July 31, 2022, was among the 10 leading causes of death in CYP aged 0 to 19 years in the US, ranking eighth among all causes of deaths, fifth in disease-related causes of deaths (excluding unintentional injuries, assault, and suicide), and first in deaths caused by infectious or respiratory diseases when compared with 2019. COVID-19 deaths constituted 2% of all causes of death in this age group. Conclusions and relevance: The findings of this study suggest that COVID-19 was a leading cause of death in CYP. It caused substantially more deaths in CYP annually than any vaccine-preventable disease historically in the recent period before vaccines became available. Various factors, including underreporting and not accounting for COVID-19's role as a contributing cause of death from other diseases, mean that these estimates may understate the true mortality burden of COVID-19. The findings of this study underscore the public health relevance of COVID-19 to CYP. In the likely future context of sustained SARS-CoV-2 circulation, appropriate pharmaceutical and nonpharmaceutical interventions (eg, vaccines, ventilation, air cleaning) will continue to play an important role in limiting transmission of the virus and mitigating severe disease in CYP.
MeSH term(s)	Child ; Humans ; Adolescent ; Cause of Death ; COVID-19 ; Cross-Sectional Studies ; SARS-CoV-2 ; Communicable Diseases
Language	English
Publishing date	2023-01-03
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2574-3805
ISSN (online)	2574-3805
DOI	10.1001/jamanetworkopen.2022.53590
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