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1. Comparison of new computational methods for geostatistical modelling of malaria

Author

Wong, Spencer, Flegg, Jennifer A., Golding, Nick, and Kandanaarachchi, Sevvandi

Subjects
Statistics - Applications
Abstract

Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods. The appeal of faster methods is particularly great as the size of the region and number of spatial locations being modelled increases. Methods We present an applied comparison of four proposed `fast' geostatistical modelling methods and the software provided to implement them -- Integrated Nested Laplace Approximation (INLA), tree boosting with Gaussian processes and mixed effect models (GPBoost), Fixed Rank Kriging (FRK) and Spatial Random Forests (SpRF). We illustrate the four methods by estimating malaria prevalence on two different spatial scales -- country and continent. We compare the performance of the four methods on these data in terms of accuracy, computation time, and ease of implementation. Results Two of these methods -- SpRF and GPBoost -- do not scale well as the data size increases, and so are likely to be infeasible for larger-scale analysis problems. The two remaining methods -- INLA and FRK -- do scale well computationally, however the resulting model fits are very sensitive to the user's modelling assumptions and parameter choices. Conclusions INLA and FRK both enable scalable geostatistical modelling of malaria prevalence data. However care must be taken when using both methods to assess the fit of the model to data and plausibility of predictions, in order to select appropriate model assumptions and approximation parameters.

Published
2023

4. Scaling multi-species occupancy models to large citizen science datasets

Author

Ingram, Martin, Vukcevic, Damjan, and Golding, Nick

Subjects
Statistics - Applications, Computer Science - Machine Learning, Statistics - Computation
Abstract

Citizen science datasets can be very large and promise to improve species distribution modelling, but detection is imperfect, risking bias when fitting models. In particular, observers may not detect species that are actually present. Occupancy models can estimate and correct for this observation process, and multi-species occupancy models exploit similarities in the observation process, which can improve estimates for rare species. However, the computational methods currently used to fit these models do not scale to large datasets. We develop approximate Bayesian inference methods and use graphics processing units (GPUs) to scale multi-species occupancy models to very large citizen science data. We fit multi-species occupancy models to one month of data from the eBird project consisting of 186,811 checklist records comprising 430 bird species. We evaluate the predictions on a spatially separated test set of 59,338 records, comparing two different inference methods -- Markov chain Monte Carlo (MCMC) and variational inference (VI) -- to occupancy models fitted to each species separately using maximum likelihood. We fitted models to the entire dataset using VI, and up to 32,000 records with MCMC. VI fitted to the entire dataset performed best, outperforming single-species models on both AUC (90.4% compared to 88.7%) and on log likelihood (-0.080 compared to -0.085). We also evaluate how well range maps predicted by the model agree with expert maps. We find that modelling the detection process greatly improves agreement and that the resulting maps agree as closely with expert maps as ones estimated using high quality survey data. Our results demonstrate that multi-species occupancy models are a compelling approach to model large citizen science datasets, and that, once the observation process is taken into account, they can model species distributions accurately., Comment: 39 pages, 6 figures (+ supplementary material)

Published
2022

5. The saturated pairwise interaction Gibbs point process as a joint species distribution model

Author

Flint, Ian, Golding, Nick, Vesk, Peter, Wang, Yan, and Xia, Aihua

Subjects
Statistics - Methodology, Mathematics - Statistics Theory
Abstract

In an effort to effectively model observed patterns in the spatial configuration of individuals of multiple species in nature, we introduce the saturated pairwise interaction Gibbs point process. Its main strength lies in its ability to model both attraction and repulsion within and between species, over different scales. As such, it is particularly well-suited to the study of associations in complex ecosystems. Based on the existing literature, we provide an easy to implement fitting procedure as well as a technique to make inference for the model parameters. We also prove that under certain hypotheses the point process is locally stable, which allows us to use the well-known `coupling from the past' algorithm to draw samples from the model. Different numerical experiments show the robustness of the model. We study three different ecological datasets, demonstrating in each one that our model helps disentangle competing ecological effects on species' distribution., Comment: 36 pages, 14 figures

Published
2022
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11. Introduction of Aedes aegypti mosquitoes carrying wAlbB Wolbachia sharply decreases dengue incidence in disease hotspots

Author

Hoffmann, Ary A., Ahmad, Nazni Wasi, Keong, Wan Ming, Ling, Cheong Yoon, Ahmad, Noor Afizah, Golding, Nick, Tierney, Nicholas, Jelip, Jenarun, Putit, Perada Wilson, Mokhtar, Norhayati, Sandhu, Sukhvinder Singh, Ming, Lau Sai, Khairuddin, Khadijah, Denim, Kamilan, Rosli, Norazman Mohd, Shahar, Hanipah, Omar, Topek, Ridhuan Ghazali, Muhammad Kamarul, Aqmar Mohd Zabari, Nur Zatil, Abdul Karim, Mohd Arif, Saidin, Mohamad Irwan, Mohd Nasir, Muhammad Nizam, Aris, Tahir, and Sinkins, Steven P.

Published
2024
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12. Assessing biophysical and socio-economic impacts of climate change on avian biodiversity

Author

Kapitza, Simon, Van Ha, Pham, Kompas, Tom, Golding, Nick, Cadenhead, Natasha C. R., Bal, Payal, and Wintle, Brendan A.

Subjects
Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods
Abstract

Climate change threatens biodiversity directly by influencing biophysical variables that drive species' geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia. We find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts, but global shifts of production are likely to result in adverse impacts on habitats worldwide. By translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global., Comment: 4 figures, 30 pages double-spaced

Published
2020

13. Temporal trends in test-seeking behaviour during the COVID-19 pandemic

Author

Eales, Oliver, primary, Teo, Mingmei, additional, Price, David J, additional, Hao, Tianxiao, additional, Ryan, Gerard E, additional, Senior, Katharine L, additional, Carlson, Sandra, additional, Dalton, Craig, additional, Dawson, Peter, additional, Golding, Nick, additional, McCaw, James M, additional, and Shearer, Freya M, additional

Published
2024
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14. The current and future global distribution and population at risk of dengue

Author

Messina, Jane P, Brady, Oliver J, Golding, Nick, Kraemer, Moritz UG, Wint, GR William, Ray, Sarah E, Pigott, David M, Shearer, Freya M, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Davis Weaver, Nicole, Gilbert, Marius, Velayudhan, Raman, Jones, Peter, Jaenisch, Thomas, Scott, Thomas W, Reiner, Robert C, and Hay, Simon I

Subjects
Microbiology, Biological Sciences, Rare Diseases, Vaccine Related, Prevention, Infectious Diseases, Emerging Infectious Diseases, Biodefense, Vector-Borne Diseases, Aetiology, 2.2 Factors relating to the physical environment, Infection, Good Health and Well Being, Aedes, Animals, Climate Change, Dengue, Dengue Virus, Geography, Medical, Global Health, Humans, Models, Statistical, Mosquito Vectors, Risk Factors, Urbanization, Medical Microbiology
Abstract

Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world's population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

Published
2019

15. Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Kraemer, Moritz UG, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Weaver, Nicole Davis, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H, Bengtsson, Linus, Wetter, Erik, Tatem, Andrew J, Brownstein, John S, Smith, David L, Lambrechts, Louis, Cauchemez, Simon, Linard, Catherine, Faria, Nuno R, Pybus, Oliver G, Scott, Thomas W, Liu, Qiyong, Yu, Hongjie, Wint, GR William, Hay, Simon I, and Golding, Nick

Subjects
Microbiology, Biological Sciences, Prevention, Good Health and Well Being, Medical Microbiology
Abstract

In the version of this Article originally published, the affiliation for author Catherine Linard was incorrectly stated as '6Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK'. The correct affiliation is '9Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium'. The affiliation for author Hongjie Yu was also incorrectly stated as '11Department of Statistics, Harvard University, Cambridge, MA, USA'. The correct affiliation is '15School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China'. This has now been amended in all versions of the Article.

Published
2019

16. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

Author

Kraemer, Moritz UG, Reiner, Robert C, Brady, Oliver J, Messina, Jane P, Gilbert, Marius, Pigott, David M, Yi, Dingdong, Johnson, Kimberly, Earl, Lucas, Marczak, Laurie B, Shirude, Shreya, Davis Weaver, Nicole, Bisanzio, Donal, Perkins, T Alex, Lai, Shengjie, Lu, Xin, Jones, Peter, Coelho, Giovanini E, Carvalho, Roberta G, Van Bortel, Wim, Marsboom, Cedric, Hendrickx, Guy, Schaffner, Francis, Moore, Chester G, Nax, Heinrich H, Bengtsson, Linus, Wetter, Erik, Tatem, Andrew J, Brownstein, John S, Smith, David L, Lambrechts, Louis, Cauchemez, Simon, Linard, Catherine, Faria, Nuno R, Pybus, Oliver G, Scott, Thomas W, Liu, Qiyong, Yu, Hongjie, Wint, GR William, Hay, Simon I, and Golding, Nick

Subjects
Microbiology, Biological Sciences, Rare Diseases, Vaccine Related, Prevention, Infectious Diseases, Emerging Infectious Diseases, Biodefense, Vector-Borne Diseases, Infection, Good Health and Well Being, Aedes, Animals, Arbovirus Infections, Arboviruses, Female, Humans, Mosquito Vectors, Medical Microbiology
Abstract

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Published
2019

19. Improving the built environment in urban areas to control Aedes aegypti -borne diseases

Author

Lindsay, Steve W, Wilson, Anne, Golding, Nick, Scott, Thomas W, and Takken, Willem

Subjects
Biomedical and Clinical Sciences, Health Sciences, Aedes, Animals, Chikungunya Fever, Dengue, Environment Design, Humans, Mosquito Vectors, Urban Population, Yellow Fever, Zika Virus Infection, Medical and Health Sciences, Tropical Medicine, Biomedical and clinical sciences, Health sciences
Published
2017

21. Data Integration for Large-Scale Models of Species Distributions

Author

Isaac, Nick J.B., Jarzyna, Marta A., Keil, Petr, Dambly, Lea I., Boersch-Supan, Philipp H., Browning, Ella, Freeman, Stephen N., Golding, Nick, Guillera-Arroita, Gurutzeta, Henrys, Peter A., Jarvis, Susan, Lahoz-Monfort, José, Pagel, Jörn, Pescott, Oliver L., Schmucki, Reto, Simmonds, Emily G., and O’Hara, Robert B.

Published
2020
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22. Mapping global environmental suitability for Zika virus.

Author

Messina, Jane P, Kraemer, Moritz Ug, Brady, Oliver J, Pigott, David M, Shearer, Freya M, Weiss, Daniel J, Golding, Nick, Ruktanonchai, Corrine W, Gething, Peter W, Cohn, Emily, Brownstein, John S, Khan, Kamran, Tatem, Andrew J, Jaenisch, Thomas, Murray, Christopher Jl, Marinho, Fatima, Scott, Thomas W, and Hay, Simon I

Subjects
Animals, Humans, Environment, Tropical Climate, Global Health, Zika Virus, Zika Virus Infection, Mosquito Vectors, Zika virus, disease mapping, epidemiology, global health, human, infectious disease, microbiology, vector-borne disease, virus, Emerging Infectious Diseases, Infectious Diseases, Rare Diseases, Vaccine Related, Vector-Borne Diseases, 2.2 Factors relating to physical environment, Infection, Biochemistry and Cell Biology
Abstract

Zika virus was discovered in Uganda in 1947 and is transmitted by Aedes mosquitoes, which also act as vectors for dengue and chikungunya viruses throughout much of the tropical world. In 2007, an outbreak in the Federated States of Micronesia sparked public health concern. In 2013, the virus began to spread across other parts of Oceania and in 2015, a large outbreak in Latin America began in Brazil. Possible associations with microcephaly and Guillain-Barré syndrome observed in this outbreak have raised concerns about continued global spread of Zika virus, prompting its declaration as a Public Health Emergency of International Concern by the World Health Organization. We conducted species distribution modelling to map environmental suitability for Zika. We show a large portion of tropical and sub-tropical regions globally have suitable environmental conditions with over 2.17 billion people inhabiting these areas.

Published
2016

24. Operationalized releases of wAlbB Wolbachia in Aedes aegypti lead to sharp decreases in dengue incidence dependent on Wolbachia frequency

Author

Hoffmann, Ary A., primary, Wasi Ahmad, Nazni, additional, Wan, Ming Keong, additional, Cheong, Yoon Ling, additional, Ahmad, Noor Afizah, additional, Golding, Nick, additional, Tierney, Nicholas, additional, Jelip, Jenarun, additional, Wilson Putit, Perada, additional, Mokhtar, Norhayati, additional, Singh Sandhu, Sukhvinder, additional, Lau, Sai Ming, additional, Khairuddin, Khadijah, additional, Denim, Kamilan, additional, Mohd Rosli, Norazman, additional, Shahar, Hanipah, additional, Omar, Topek, additional, Ridhuan Ghazali, Muhammad Kamarul, additional, Mohd Zabari, Nur Zatil Aqmar, additional, Abdul Karim, Mohd Arif, additional, Saidin, Mohamad Irwan, additional, Mohd Nasir, Muhammad Nizam, additional, Aris, Tahir, additional, and Sinkins, Steven P, additional

Published
2023
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27. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus.

Author

Kraemer, Moritz UG, Sinka, Marianne E, Duda, Kirsten A, Mylne, Adrian QN, Shearer, Freya M, Barker, Christopher M, Moore, Chester G, Carvalho, Roberta G, Coelho, Giovanini E, Van Bortel, Wim, Hendrickx, Guy, Schaffner, Francis, Elyazar, Iqbal RF, Teng, Hwa-Jen, Brady, Oliver J, Messina, Jane P, Pigott, David M, Scott, Thomas W, Smith, David L, Wint, GR William, Golding, Nick, and Hay, Simon I

Subjects
Animals, Humans, Aedes, Arbovirus Infections, Insect Vectors, Phylogeography, Global Health, Ae. aegypti, Ae. albopictus, ecology, epidemiology, global health, Biochemistry and Cell Biology
Abstract

Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.

Published
2015

28. Mapping the distribution of Nipah virus infections: a geospatial modelling analysis

Author

Sun, Yan-Qun, Zhang, Yuan-Yuan, Liu, Mei-Chen, Chen, Jin-Jin, Li, Ting-Ting, Liu, Yan-Ning, Zhang, Ling-Yu, Wang, Tao, Yu, Lin-Jie, Che, Tian-Le, Tang, Tian, Xu, Qiang, Lv, Chen-Long, Jiang, Bao-Gui, Golding, Nick, Mehlman, Max L, Hay, Simon I, Fang, Li-Qun, and Liu, Wei

Abstract

Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.

Published
2024
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29. Global temperature constraints on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission.

Author

Brady, Oliver J, Golding, Nick, Pigott, David M, Kraemer, Moritz UG, Messina, Jane P, Reiner, Robert C, Scott, Thomas W, Smith, David L, Gething, Peter W, and Hay, Simon I

Subjects
Animals, Aedes, Dengue Virus, Dengue, Temperature, Seasons, Models, Biological, Global Health, Aegypti, Albopictus, Distribution, Suitability, Competence, Disease model, Map, Models, Biological, Tropical Medicine, Mycology & Parasitology, Medical Microbiology, Public Health and Health Services
Abstract

BackgroundDengue is a disease that has undergone significant expansion over the past hundred years. Understanding what factors limit the distribution of transmission can be used to predict current and future limits to further dengue expansion. While not the only factor, temperature plays an important role in defining these limits. Previous attempts to analyse the effect of temperature on the geographic distribution of dengue have not considered its dynamic intra-annual and diurnal change and its cumulative effects on mosquito and virus populations.MethodsHere we expand an existing modelling framework with new temperature-based relationships to model an index proportional to the basic reproductive number of the dengue virus. This model framework is combined with high spatial and temporal resolution global temperature data to model the effects of temperature on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission.ResultsOur model predicted areas where temperature is not expected to permit transmission and/or Aedes persistence throughout the year. By reanalysing existing experimental data our analysis indicates that Ae. albopictus, often considered a minor vector of dengue, has comparable rates of virus dissemination to its primary vector, Ae. aegypti, and when the longer lifespan of Ae. albopictus is considered its competence for dengue virus transmission far exceeds that of Ae. aegypti.ConclusionsThese results can be used to analyse the effects of temperature and other contributing factors on the expansion of dengue or its Aedes vectors. Our finding that Ae. albopictus has a greater capacity for dengue transmission than Ae. aegypti is contrary to current explanations for the comparative rarity of dengue transmission in established Ae. albopictus populations. This suggests that the limited capacity of Ae. albopictus to transmit DENV is more dependent on its ecology than vector competence. The recommendations, which we explicitly outlined here, point to clear targets for entomological investigation.

Published
2014

30. COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting

Author

Conway, Eamon, primary, Walker, Camelia R., additional, Baker, Christopher, additional, Lydeamore, Michael J., additional, Ryan, Gerard E., additional, Campbell, Trish, additional, Miller, Joel C., additional, Rebuli, Nic, additional, Yeung, Max, additional, Kabashima, Greg, additional, Geard, Nicholas, additional, Wood, James, additional, McCaw, James M., additional, McVernon, Jodie, additional, Golding, Nick, additional, Price, David J., additional, and Shearer, Freya M., additional

Published
2023
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31. Modelling adult Aedes aegypti and Aedes albopictus survival at different temperatures in laboratory and field settings

Author

Brady, Oliver J, Johansson, Michael A, Guerra, Carlos A, Bhatt, Samir, Golding, Nick, Pigott, David M, Delatte, Hélène, Grech, Marta G, Leisnham, Paul T, Maciel-de-Freitas, Rafael, Styer, Linda M, Smith, David L, Scott, Thomas W, Gething, Peter W, and Hay, Simon I

Abstract

Abstract Background The survival of adult female Aedes mosquitoes is a critical component of their ability to transmit pathogens such as dengue viruses. One of the principal determinants of Aedes survival is temperature, which has been associated with seasonal changes in Aedes populations and limits their geographical distribution. The effects of temperature and other sources of mortality have been studied in the field, often via mark-release-recapture experiments, and under controlled conditions in the laboratory. Survival results differ and reconciling predictions between the two settings has been hindered by variable measurements from different experimental protocols, lack of precision in measuring survival of free-ranging mosquitoes, and uncertainty about the role of age-dependent mortality in the field. Methods Here we apply generalised additive models to data from 351 published adult Ae. aegypti and Ae. albopictus survival experiments in the laboratory to create survival models for each species across their range of viable temperatures. These models are then adjusted to estimate survival at different temperatures in the field using data from 59 Ae. aegypti and Ae. albopictus field survivorship experiments. The uncertainty at each stage of the modelling process is propagated through to provide confidence intervals around our predictions. Results Our results indicate that adult Ae. albopictus has higher survival than Ae. aegypti in the laboratory and field, however, Ae. aegypti can tolerate a wider range of temperatures. A full breakdown of survival by age and temperature is given for both species. The differences between laboratory and field models also give insight into the relative contributions to mortality from temperature, other environmental factors, and senescence and over what ranges these factors can be important. Conclusions Our results support the importance of producing site-specific mosquito survival estimates. By including fluctuating temperature regimes, our models provide insight into seasonal patterns of Ae. aegypti and Ae. albopictus population dynamics that may be relevant to seasonal changes in dengue virus transmission. Our models can be integrated with Aedes and dengue modelling efforts to guide and evaluate vector control, better map the distribution of disease and produce early warning systems for dengue epidemics.

Published
2013

33. Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis

Author

Shearer, Freya M, Longbottom, Joshua, Browne, Annie J, Pigott, David M, Brady, Oliver J, Kraemer, Moritz U G, Marinho, Fatima, Yactayo, Sergio, de Araújo, Valdelaine E M, da Nóbrega, Aglaêr A, Fullman, Nancy, Ray, Sarah E, Mosser, Jonathan F, Stanaway, Jeffrey D, Lim, Stephen S, Reiner, Robert C, Jr, Moyes, Catherine L, Hay, Simon I, and Golding, Nick

Published
2018
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34. Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Author

Burstein, Roy, Henry, Nathaniel J., Collison, Michael L., Marczak, Laurie B., Sligar, Amber, Watson, Stefanie, Marquez, Neal, Abbasalizad-Farhangi, Mahdieh, Abbasi, Masoumeh, Abd-Allah, Foad, Abdoli, Amir, Abdollahi, Mohammad, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abrigo, Michael R. M., Acharya, Dilaram, Adebayo, Oladimeji M., Adekanmbi, Victor, Adham, Davoud, Afshari, Mahdi, Aghaali, Mohammad, Ahmadi, Keivan, Ahmadi, Mehdi, Ahmadpour, Ehsan, Ahmed, Rushdia, Akal, Chalachew Genet, Akinyemi, Joshua O., Alahdab, Fares, Alam, Noore, Alamene, Genet Melak, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alinia, Cyrus, Alipour, Vahid, Aljunid, Syed Mohamed, Almalki, Mohammed J., Al-Mekhlafi, Hesham M., Altirkawi, Khalid, Alvis-Guzman, Nelson, Amegah, Adeladza Kofi, Amini, Saeed, Amit, Arianna Maever Loreche, Anbari, Zohreh, Androudi, Sofia, Anjomshoa, Mina, Ansari, Fereshteh, Antonio, Carl Abelardo T., Arabloo, Jalal, Arefi, Zohreh, Aremu, Olatunde, Armoon, Bahram, Arora, Amit, Artaman, Al, Asadi, Anvar, Asadi-Aliabadi, Mehran, Ashraf-Ganjouei, Amir, Assadi, Reza, Ataeinia, Bahar, Atre, Sachin R., Quintanilla, Beatriz Paulina Ayala, Ayanore, Martin Amogre, Azari, Samad, Babaee, Ebrahim, Babazadeh, Arefeh, Badawi, Alaa, Bagheri, Soghra, Bagherzadeh, Mojtaba, Baheiraei, Nafiseh, Balouchi, Abbas, Barac, Aleksandra, Bassat, Quique, Baune, Bernhard T., Bayati, Mohsen, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Belay, Yared Belete, Bell, Brent, Bell, Michelle L., Berbada, Dessalegn Ajema, Bernstein, Robert S., Bhattacharjee, Natalia V., Bhattarai, Suraj, Bhutta, Zulfiqar A., Bijani, Ali, Bohlouli, Somayeh, Breitborde, Nicholas J. K., Britton, Gabrielle, Browne, Annie J., Nagaraja, Sharath Burugina, Busse, Reinhard, Butt, Zahid A., Car, Josip, Cárdenas, Rosario, Castañeda-Orjuela, Carlos A., Cerin, Ester, Chanie, Wagaye Fentahun, Chatterjee, Pranab, Chu, Dinh-Toi, Cooper, Cyrus, Costa, Vera M., Dalal, Koustuv, Dandona, Lalit, Dandona, Rakhi, Daoud, Farah, Daryani, Ahmad, Das Gupta, Rajat, Davis, Ian, Davis Weaver, Nicole, Davitoiu, Dragos Virgil, De Neve, Jan-Walter, Demeke, Feleke Mekonnen, Demoz, Gebre Teklemariam, Deribe, Kebede, Desai, Rupak, Deshpande, Aniruddha, Desyibelew, Hanna Demelash, Dey, Sagnik, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Diaz, Daniel, Doshmangir, Leila, Duraes, Andre R., Dwyer-Lindgren, Laura, Earl, Lucas, Ebrahimi, Roya, Ebrahimpour, Soheil, Effiong, Andem, Eftekhari, Aziz, Ehsani-Chimeh, Elham, El Sayed, Iman, El Sayed Zaki, Maysaa, El Tantawi, Maha, El-Khatib, Ziad, Emamian, Mohammad Hassan, Enany, Shymaa, Eskandarieh, Sharareh, Eyawo, Oghenowede, Ezalarab, Maha, Faramarzi, Mahbobeh, Fareed, Mohammad, Faridnia, Roghiyeh, Faro, Andre, Fazaeli, Ali Akbar, Fazlzadeh, Mehdi, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, João C., Filip, Irina, Fischer, Florian, Foigt, Nataliya A., Foroutan, Masoud, Francis, Joel Msafiri, Fukumoto, Takeshi, Fullman, Nancy, Gallus, Silvano, Gebre, Destallem Gebremedhin, Gebrehiwot, Tsegaye Tewelde, Gebremeskel, Gebreamlak Gebremedhn, Gessner, Bradford D., Geta, Birhanu, Gething, Peter W., Ghadimi, Reza, Ghadiri, Keyghobad, Ghajarzadeh, Mahsa, Ghashghaee, Ahmad, Gill, Paramjit Singh, Gill, Tiffany K., Golding, Nick, Gomes, Nelson G. M., Gona, Philimon N., Gopalani, Sameer Vali, Gorini, Giuseppe, Goulart, Bárbara Niegia Garcia, Graetz, Nicholas, Greaves, Felix, Green, Manfred S., Guo, Yuming, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hall, Brian James, Hamidi, Samer, Haririan, Hamidreza, Haro, Josep Maria, Hasankhani, Milad, Hasanpoor, Edris, Hasanzadeh, Amir, Hassankhani, Hadi, Hassen, Hamid Yimam, Hegazy, Mohamed I., Hendrie, Delia, Heydarpour, Fatemeh, Hird, Thomas R., Hoang, Chi Linh, Hollerich, Gillian, Rad, Enayatollah Homaie, Hoseini-Ghahfarokhi, Mojtaba, Hossain, Naznin, Hosseini, Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Househ, Mowafa, Hsairi, Mohamed, Ilesanmi, Olayinka Stephen, Imani-Nasab, Mohammad Hasan, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Islam, Nazrul, Islam, Sheikh Mohammed Shariful, Jürisson, Mikk, Balalami, Nader Jafari, Jalali, Amir, Javidnia, Javad, Jayatilleke, Achala Upendra, Jenabi, Ensiyeh, Ji, John S., Jobanputra, Yash B., Johnson, Kimberly, Jonas, Jost B., Shushtari, Zahra Jorjoran, Jozwiak, Jacek Jerzy, Kabir, Ali, Kahsay, Amaha, Kalani, Hamed, Kalhor, Rohollah, Karami, Manoochehr, Karki, Surendra, Kasaeian, Amir, Kassebaum, Nicholas J., Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Khabiri, Roghayeh, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khan, Ejaz Ahmad, Khan, Junaid, Khan, Muhammad Shahzeb, Khang, Young-Ho, Khatab, Khaled, Khater, Amir, Khater, Mona M., Khatony, Alireza, Khazaei, Mohammad, Khazaei, Salman, Khazaei-Pool, Maryam, Khubchandani, Jagdish, Kianipour, Neda, Kim, Yun Jin, Kimokoti, Ruth W., Kinyoki, Damaris K., Kisa, Adnan, Kisa, Sezer, Kolola, Tufa, Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kraemer, Moritz U. G., Krishan, Kewal, Krohn, Kris J., Kugbey, Nuworza, Kumar, G. Anil, Kumar, Manasi, Kumar, Pushpendra, Kuupiel, Desmond, Lacey, Ben, Lad, Sheetal D., Lami, Faris Hasan, Larsson, Anders O., Lee, Paul H., Leili, Mostafa, Levine, Aubrey J., Li, Shanshan, Lim, Lee-Ling, Listl, Stefan, Longbottom, Joshua, Lopez, Jaifred Christian F., Lorkowski, Stefan, Magdeldin, Sameh, Abd El Razek, Hassan Magdy, Abd El Razek, Muhammed Magdy, Majeed, Azeem, Maleki, Afshin, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A., Manafi, Navid, Manda, Ana-Laura, Mansourian, Morteza, Martins-Melo, Francisco Rogerlândio, Masaka, Anthony, Massenburg, Benjamin Ballard, Maulik, Pallab K., Mayala, Benjamin K., Mazidi, Mohsen, McKee, Martin, Mehrotra, Ravi, Mehta, Kala M., Meles, Gebrekiros Gebremichael, Mendoza, Walter, Menezes, Ritesh G., Meretoja, Atte, Meretoja, Tuomo J., Mestrovic, Tomislav, Miller, Ted R., Miller-Petrie, Molly K., Mills, Edward J., Milne, George J., Mini, G. K., Mir, Seyed Mostafa, Mirjalali, Hamed, Mirrakhimov, Erkin M., Mohamadi, Efat, Mohammad, Dara K., Darwesh, Aso Mohammad, Mezerji, Naser Mohammad Gholi, Mohammed, Ammas Siraj, Mohammed, Shafiu, Mokdad, Ali H., Molokhia, Mariam, Monasta, Lorenzo, Moodley, Yoshan, Moosazadeh, Mahmood, Moradi, Ghobad, Moradi, Masoud, Moradi, Yousef, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Mosapour, Abbas, Mousavi, Seyyed Meysam, Mueller, Ulrich Otto, Muluneh, Atalay Goshu, Mustafa, Ghulam, Nabavizadeh, Behnam, Naderi, Mehdi, Nagarajan, Ahamarshan Jayaraman, Nahvijou, Azin, Najafi, Farid, Nangia, Vinay, Ndwandwe, Duduzile Edith, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W., Thi Nguyen, Huong Lan, Nguyen, Long Hoang, Nguyen, Son Hoang, Nielsen, Katie R., Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nixon, Molly R., Nnaji, Chukwudi A., Nojomi, Marzieh, Noroozi, Mehdi, Nosratnejad, Shirin, Noubiap, Jean Jacques, Motlagh, Soraya Nouraei, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oladimeji, Kelechi E., Olagunju, Andrew T., Olfatifar, Meysam, Olum, Solomon, Olusanya, Bolajoko Olubukunola, Oluwasanu, Mojisola Morenike, Onwujekwe, Obinna E., Oren, Eyal, Ortega-Altamirano, Doris D. V., Ortiz, Alberto, Osarenotor, Osayomwanbo, Osei, Frank B., Osgood-Zimmerman, Aaron E., Otstavnov, Stanislav S., Owolabi, Mayowa Ojo, P. A., Mahesh, Pagheh, Abdol Sattar, Pakhale, Smita, Panda-Jonas, Songhomitra, Pandey, Animika, Park, Eun-Kee, Parsian, Hadi, Pashaei, Tahereh, Patel, Sangram Kishor, Pepito, Veincent Christian Filipino, Pereira, Alexandre, Perkins, Samantha, Pickering, Brandon V., Pilgrim, Thomas, Pirestani, Majid, Piroozi, Bakhtiar, Pirsaheb, Meghdad, Plana-Ripoll, Oleguer, Pourjafar, Hadi, Puri, Parul, Qorbani, Mostafa, Quintana, Hedley, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafiei, Alireza, Rahim, Fakher, Rahimi, Zohreh, Rahimi-Movaghar, Vafa, Rahimzadeh, Shadi, Rajati, Fatemeh, Raju, Sree Bhushan, Ramezankhani, Azra, Ranabhat, Chhabi Lal, Rasella, Davide, Rashedi, Vahid, Rawal, Lal, Reiner Jr, Robert C., Renzaho, Andre M. N., Rezaei, Satar, Rezapour, Aziz, Riahi, Seyed Mohammad, Ribeiro, Ana Isabel, Roever, Leonardo, Roro, Elias Merdassa, Roser, Max, Roshandel, Gholamreza, Roshani, Daem, Rostami, Ali, Rubagotti, Enrico, Rubino, Salvatore, Sabour, Siamak, Sadat, Nafis, Sadeghi, Ehsan, Saeedi, Reza, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Sahebkar, Amirhossein, Salahshoor, Mohammad Reza, Salam, Nasir, Salamati, Payman, Salehi, Farkhonde, Zahabi, Saleh Salehi, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A., Sambala, Evanson Zondani, Samy, Abdallah M., Santric Milicevic, Milena M., Jose, Bruno Piassi Sao, Saraswathy, Sivan Yegnanarayana Iyer, Sarmiento-Suárez, Rodrigo, Sartorius, Benn, Sathian, Brijesh, Saxena, Sonia, Sbarra, Alyssa N., Schaeffer, Lauren E., Schwebel, David C., Sepanlou, Sadaf G., Seyedmousavi, Seyedmojtaba, Shaahmadi, Faramarz, Shaikh, Masood Ali, Shams-Beyranvand, Mehran, Shamshirian, Amir, Shamsizadeh, Morteza, Sharafi, Kiomars, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharifi, Hamid, Sharma, Jayendra, Sharma, Rajesh, Sheikh, Aziz, Shields, Chloe, Shigematsu, Mika, Shiri, Rahman, Shiue, Ivy, Shuval, Kerem, Siddiqi, Tariq J., Silva, João Pedro, Singh, Jasvinder A., Sinha, Dhirendra Narain, Sisay, Malede Mequanent, Sisay, Solomon, Sliwa, Karen, Smith, David L., Somayaji, Ranjani, Soofi, Moslem, Soriano, Joan B., Sreeramareddy, Chandrashekhar T., Sudaryanto, Agus, Sufiyan, Mu’awiyyah Babale, Sykes, Bryan L., Sylaja, P. N., Tabarés-Seisdedos, Rafael, Tabb, Karen M., Tabuchi, Takahiro, Taveira, Nuno, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tessema, Zemenu Tadesse, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, To, Quyen G., Tovani-Palone, Marcos Roberto, Tran, Bach Xuan, Tran, Khanh Bao, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A., Vahedian-Azimi, Amir, Valdez, Pascual R., van Boven, Job F. M., Vasankari, Tommi Juhani, Vasseghian, Yasser, Veisani, Yousef, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vos, Theo, Vu, Giang Thu, Vujcic, Isidora S., Waheed, Yasir, Wakefield, Jon, Wang, Haidong, Wang, Yafeng, Wang, Yuan-Pang, Ward, Joseph L., Weintraub, Robert G., Weldegwergs, Kidu Gidey, Weldesamuel, Girmay Teklay, Westerman, Ronny, Wiysonge, Charles Shey, Wondafrash, Dawit Zewdu, Woyczynski, Lauren, Wu, Ai-Min, Xu, Gelin, Yadegar, Abbas, Yamada, Tomohide, Yazdi-Feyzabadi, Vahid, Yilgwan, Christopher Sabo, Yip, Paul, Yonemoto, Naohiro, Lebni, Javad Yoosefi, Younis, Mustafa Z., Yousefifard, Mahmoud, Yousof, Hebat-Allah Salah A., Yu, Chuanhua, Yusefzadeh, Hasan, Zabeh, Erfan, Moghadam, Telma Zahirian, Bin Zaman, Sojib, Zamani, Mohammad, Zandian, Hamed, Zangeneh, Alireza, Zerfu, Taddese Alemu, Zhang, Yunquan, Ziapour, Arash, Zodpey, Sanjay, Murray, Christopher J. L., and Hay, Simon I.

Published
2019
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35. Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis

Author

Pigott, David M, Deshpande, Aniruddha, Letourneau, Ian, Morozoff, Chloe, Reiner, Robert C, Jr, Kraemer, Moritz U G, Brent, Shannon E, Bogoch, Isaac I, Khan, Kamran, Biehl, Molly H, Burstein, Roy, Earl, Lucas, Fullman, Nancy, Messina, Jane P, Mylne, Adrian Q N, Moyes, Catherine L, Shearer, Freya M, Bhatt, Samir, Brady, Oliver J, Gething, Peter W, Weiss, Daniel J, Tatem, Andrew J, Caley, Luke, De Groeve, Tom, Vernaccini, Luca, Golding, Nick, Horby, Peter, Kuhn, Jens H, Laney, Sandra J, Ng, Edmond, Piot, Peter, Sankoh, Osman, Murray, Christopher J L, and Hay, Simon I

Published
2017
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36. Mapping under-5 and neonatal mortality in Africa, 2000–15: a baseline analysis for the Sustainable Development Goals

Author

Golding, Nick, Burstein, Roy, Longbottom, Joshua, Browne, Annie J, Fullman, Nancy, Osgood-Zimmerman, Aaron, Earl, Lucas, Bhatt, Samir, Cameron, Ewan, Casey, Daniel C, Dwyer-Lindgren, Laura, Farag, Tamer H, Flaxman, Abraham D, Fraser, Maya S, Gething, Peter W, Gibson, Harry S, Graetz, Nicholas, Krause, L Kendall, Kulikoff, Xie Rachel, Lim, Stephen S, Mappin, Bonnie, Morozoff, Chloe, Reiner, Robert C, Jr, Sligar, Amber, Smith, David L, Wang, Haidong, Weiss, Daniel J, Murray, Christopher J L, Moyes, Catherine L, and Hay, Simon I

Published
2017
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37. Global yellow fever vaccination coverage from 1970 to 2016: an adjusted retrospective analysis

Author

Shearer, Freya M, Moyes, Catherine L, Pigott, David M, Brady, Oliver J, Marinho, Fatima, Deshpande, Aniruddha, Longbottom, Joshua, Browne, Annie J, Kraemer, Moritz U G, O'Reilly, Kathleen M, Hombach, Joachim, Yactayo, Sergio, de Araújo, Valdelaine E M, da Nóbrega, Aglaêr A, Mosser, Jonathan F, Stanaway, Jeffrey D, Lim, Stephen S, Hay, Simon I, Golding, Nick, and Reiner, Robert C, Jr

Published
2017
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38. Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015–16: a modelling study

Author

Kraemer, Moritz U G, Faria, Nuno R, Reiner, Robert C, Jr, Golding, Nick, Nikolay, Birgit, Stasse, Stephanie, Johansson, Michael A, Salje, Henrik, Faye, Ousmane, Wint, G R William, Niedrig, Matthias, Shearer, Freya M, Hill, Sarah C, Thompson, Robin N, Bisanzio, Donal, Taveira, Nuno, Nax, Heinrich H, Pradelski, Bary S R, Nsoesie, Elaine O, Murphy, Nicholas R, Bogoch, Isaac I, Khan, Kamran, Brownstein, John S, Tatem, Andrew J, de Oliveira, Tulio, Smith, David L, Sall, Amadou A, Pybus, Oliver G, Hay, Simon I, and Cauchemez, Simon

Published
2017
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39. Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans

Author

Vandelannoote, Koen, primary, Buultjens, Andrew H, primary, Porter, Jessica L, additional, Velink, Anita, additional, Wallace, John R, additional, Blasdell, Kim R, additional, Dunn, Michael, additional, Boyd, Victoria, additional, Fyfe, Janet AM, additional, Tay, Ee Laine, additional, Johnson, Paul DR, additional, Windecker, Saras M, additional, Golding, Nick, additional, and Stinear, Timothy P, additional

Published
2023
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40. Author response: Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans

Author

Vandelannoote, Koen, primary, Buultjens, Andrew H, primary, Porter, Jessica L, additional, Velink, Anita, additional, Wallace, John R, additional, Blasdell, Kim R, additional, Dunn, Michael, additional, Boyd, Victoria, additional, Fyfe, Janet AM, additional, Tay, Ee Laine, additional, Johnson, Paul DR, additional, Windecker, Saras M, additional, Golding, Nick, additional, and Stinear, Timothy P, additional

Published
2023
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41. A modelling approach to estimate the transmissibility of SARS-CoV 2 during periods of high, low, and zero case incidence

Author

Golding, Nick, Price, D.J., Ryan, G.E., McVernon, J., McCaw, J.M., Shearer, F.M., Golding, Nick, Price, D.J., Ryan, G.E., McVernon, J., McCaw, J.M., and Shearer, F.M.

Abstract

Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the effective reproduction number can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low – or zero – case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low – or zero – case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.

Published
2023

47. COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting

Author

Conway, Eamon, primary, Walker, Camelia, additional, Baker, Chris, additional, Lydeamore, Michael, additional, Ryan, Gerard E., additional, Campbell, Trish, additional, Miller, Joel C., additional, Yeung, Max, additional, Kabashima, Greg, additional, Wood, James, additional, Rebuli, Nic, additional, McCaw, James M., additional, McVernon, Jodie, additional, Golding, Nick, additional, Price, David J., additional, and Shearer, Freya M., additional

Published
2022
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48. Structured surveys of Australian native possum excreta predict Buruli ulcer occurrence in humans

Author

Vandelannoote, Koen, primary, Buultjens, Andrew H., additional, Porter, Jessica L., additional, Velink, Anita, additional, Wallace, John R., additional, Blasdell, Kim R., additional, Dunn, Michael, additional, Boyd, Victoria, additional, Fyfe, Janet A. M., additional, Tay, Ee Laine, additional, Johnson, Paul D. R., additional, Windecker, Saras, additional, Golding, Nick, additional, and Stinear, Timothy P., additional

Published
2022
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