@article{nokey,

title = {A stochastic approach to integerize floating-point estimates in gridded population mapping},

author = {Wenbin Zhang and Alessandro Sorichetta and Charlie Frye and Natalia Tejedor-Garavito and Weixuan Fang and Duygu Cihan and Dorothea Woods and Gregory Yetman and Jason Hilton and Andrew J. Tatem and Maksym Bondarenko},

url = {https://doi.org/10.1080/13658816.2025.2568721},

doi = {10.1080/13658816.2025.2568721},

year  = {2025},

date = {2025-10-01},

journal = {International Journal of Geographical Information Science},

pages = {1–17},

abstract = {Gridded population datasets are increasingly relied upon for spatial planning, resource allocation, and disaster response due to their flexible integration with other spatial data layers. These datasets are typically produced by disaggregating population counts from administrative units into grid cells, yielding non-integer values that preserve overall counts. However, floating-point cell values are often difficult for users to interpret, and standard rounding approaches may introduce aggregation errors at administrative levels that affect planning decisions. Here, we present a stochastic integerisation method that preserves total population and demographic proportions, and compare it with existing approaches. The method separates the value of each cell into integer and decimal parts, and probabilistically allocates the residual based on decimal magnitudes. Applying the method to gridded population data shows that it effectively reduces unrealistic population predictions in uninhabited areas. The results also demonstrate that the new integerisation method can effectively convert floating-point population estimates into integers while preserving both spatial distribution and demographic proportions, such as age-sex structures. These findings highlight the performance of the proposed integerisation method to generate reliable gridded population distribution datasets across diverse contexts that are easier to interpret, particularly for areas with sparse populations or complex geometries of underlying administrative units.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Tackling public health data gaps through Bayesian high-resolution population estimation: A case study of Kasaï-Oriental, Democratic Republic of the Congo},

author = {Gianluca Boo and Edith Darin and Heather R. Chamberlain and Roland Hosner and Pierre K. Akilimali and Henri Marie Kazadi and Chibuzor C. Nnanatu and Attila N. Lázár and Andrew J. Tatem},

url = {https://doi.org/10.1371/journal.pgph.0005072},

year  = {2025},

date = {2025-09-04},

journal = {PLOS Global Public Health },

abstract = {Most low- and middle-income countries face significant public health challenges, exacerbated by the lack of reliable demographic data supporting effective planning and intervention. In such data-scarce settings, statistical models combining geolocated survey data with geospatial datasets enable the estimation of population counts at high spatial resolution in the absence of dependable demographic data sources. This study introduces a Bayesian model jointly estimating building and population counts, combining geolocated survey data and gridded geospatial datasets. The model provides population estimates for the Kasaï-Oriental province, Democratic Republic of the Congo (DRC), at a spatial resolution of approximately one hectare. Posterior estimates are aggregated across health zones and health areas to offer probabilistic insights into their respective populations. The model exhibits a –0.28 bias, 0.47 inaccuracy, and 0.95 imprecision using scaled residuals, with robust 95% credible intervals. The estimated population of Kasaï-Oriental for 2024 is approximately 4.1 million, with a credible range of 3.4 to 4.8 million. Aggregations by health zones and health areas reveal significant variations in population estimates and uncertainty levels, particularly between the provincial capital, Mbuji-Mayi and the rural hinterland. High-resolution Bayesian population estimates allow flexible aggregation across spatial units while providing probabilistic insights into model uncertainty. These estimates offer a unique resource for the public health community working in Kasaï-Oriental, for instance, in support of a better-informed allocation of vaccines to different operational boundaries based on the upper bound of the 95% credible intervals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Geostatistical and machine learning approaches for high-resolution mapping of vaccination coverage},

author = {C. Edson Utazi and Ortis Yankey and Somnath Chaudhuri and Iyanuloluwa D. Olowe and M. Carolina Danovaro-Holliday and Attila N. Lazar and Andrew J. Tatem},

url = {https://doi.org/10.1016/j.sste.2025.100744},

year  = {2025},

date = {2025-08-23},

journal = {Spatial and Spatio-temporal Epidemiology},

volume = {54},

number = {100744},

abstract = {Recently, there has been a growing interest in the production of high-resolution maps of vaccination coverage. These maps have been useful for uncovering geographic inequities in coverage and improving targeting of interventions to reach marginalized populations. Different methodological approaches have been developed for producing these maps using mostly geolocated household survey data and geospatial covariate information. However, it remains unclear how much the predicted coverage maps produced by the various methods differ, and which methods yield more reliable estimates. Here, we explore the predictive performance of these methods and resulting implications for spatial prioritization to fill this gap. Using Nigeria Demographic and Health Survey as a case study, we generate 1 × 1 km and district level maps of indicators of vaccination coverage using geostatistical, machine learning (ML) and hybrid methods and evaluate predictive performance via cross-validation. Our results show similar predictive performance for five of the seven methods investigated, although two geostatistical approaches are the best performing methods. The worst-performing methods are two ML approaches. We find marked differences in spatial prioritization using these methods, which could potentially result in missing important underserved populations, although broad similarities exist. Our study can help guide map production for other health and development metrics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Serological survey to determine measles and rubella immunity gaps across age and geographic locations in The Gambia: a study protocol},

author = {Oghenebrume Wariri and Abdul Khalie Muhammad and Alieu Sowe and Julia Strandmark and Chigozie Edson Utazi and C Jessica E Metcalf and Beate Kampmann},

doi = {10.1080/16549716.2025.2540135},

year  = {2025},

date = {2025-08-20},

journal = {Global Health Action},

volume = {18},

issue = {1},

abstract = {Vaccine coverage and disease surveillance data are valuable for monitoring protection against vaccine-preventable diseases; however, they do not directly measure population immunity. High-quality, representative serological studies can provide key insights into immunity gaps, outbreak susceptibility, and inform targeted vaccination strategies, even in high-performing immunization programs. This study aims to estimate location-specific and age-specific immunity profiles for measles and rubella while evaluating the predictive value of indirect immunity estimates derived from vaccination and surveillance data against direct serological measurements. Additionally, it seeks to model the risk of measles outbreaks and assess the impact of mitigation strategies. A multi-stage, stratified cluster sampling design will be implemented across six districts in The Gambia's North Bank and Upper River Regions. Survey clusters (i.e. 5 km × 5 km areas) encompassing all settlements within their boundaries will be selected, proportionally to district population sizes. Cluster selection ensures representativeness of both the population and vaccine coverage within each district. Based on detecting a 10% difference in protective immunity across vaccine coverage levels, power analysis assumes an intraclass correlation coefficient (ICC) of 0.01. In each cluster, 70 children aged 9 months to 14 years will be recruited, yielding a total sample size of 1,750 children across 25 selected clusters. Dried blood samples will be collected and tested for anti-measles and anti-rubella IgG using enzyme immunoassays (EIA). District-specific measles seroprevalence will be estimated using a hierarchical spatial model. This study will generate key evidence needed to refine immunization strategies and reduce the risk of measles and rubella outbreaks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Integrating vulnerability and hazard in malaria risk mapping: the elimination context of Senegal},

author = {Camille Morlighem and Chibuzor Christopher Nnanatu and Justice Moses K. Aheto and Catherine Linard },

url = {https://doi.org/10.1186/s12879-025-11412-5},

year  = {2025},

date = {2025-08-18},

journal = {BMC Infectious Diseases},

volume = {25},

number = {1031},

abstract = {Significant efforts over the past decades have successfully reduced the global burden of malaria. However, progress has stalled since 2015. In low-transmission settings, the traditional distribution of malaria along vector suitability gradients is shifting to a new profile, with the emergence of hotspots where the disease persists. To support elimination in this context, it is essential that malaria risk maps consider not only environmental and climatic factors, but also societal vulnerabilities, in order to identify remaining hotspots and ensure that no contributing factors are overlooked. In this paper, we present an integrated approach to malaria risk mapping based on the decomposition of malaria risk into two components: ‘hazard’, which refers to the potential presence of infected vectors (e.g. influenced by rainfall and temperature), and ‘vulnerability’, which is the predisposition of the population to the burden of malaria (e.g. related to health care access and housing conditions). We focus on Senegal, which has a heterogeneous malaria epidemiological profile, ranging from high transmission in the south-east to very low transmission in the north, and which aims to eliminate malaria by 2030.



We combined data from several sources: the 2017 Demographic and Health Survey (DHS) (national coverage) and the 2020-21 Malaria Indicator Survey (MIS) (south-east regions), as well as remotely sensed, high-resolution covariate data. Using Bayesian geostatistical models, we predicted the prevalence of malaria in children under five years of age with a spatial resolution of 1 km.



Including vulnerability factors alongside hazard factors in the 2017 DHS data model improved the accuracy of predictive maps, achieving a median predictive R² of 0.64. Furthermore, models including only vulnerability factors outperformed those including only hazard factors. However, the models trained on the 2020-21 MIS data performed poorly, achieving a median R² of 0.13 at best for the model based on hazard factors, likely due to data collection during the dry season.



These findings highlight the importance of integrating both vulnerability and hazard factors into predictive maps. Future work could validate this approach further using routine malaria data from health management information systems, such as DHIS2.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Future heat-related mortality in Europe driven by compound day-night heatwaves and demographic shifts},

author = {Xilin Wu and Jun Wang and Yong Ge and Shengjie Lai and Die Zhang and Zhoupeng Ren and Jianghao Wang },

url = {https://doi.org/10.1038/s41467-025-62871-y},

year  = {2025},

date = {2025-08-11},

journal = {Nature Communications},

volume = {16},

number = {7420},

abstract = {Anthropogenic climate change is driving summer heat toward more humid conditions, accompanied by more frequent day-night compound heat extremes (high temperatures during both day and night). As the fast-warming and aging continent, Europe faces escalating heat-related health risks. Here, we projected future heat-related mortality in Europe using a distributed lag nonlinear model that incorporates humid heat and compound heat extremes, strengthened by a health risk-based definition of extreme heat and a scenario matrix integrating time-varying adaptation trajectories. Under 2010–2019 adaptation baselines, future heat-related mortality is projected to increase annually by 103.7-135.1 deaths per million people by 2100 across various population-climate scenarios for every degree of global warming, with Western and Eastern Europe suffering the most. If global warming exceeds 2 °C, climate change will dominate (84.0–96.8%) projected increase in heat-related mortality. Across all socioeconomic pathways, even a 50% reduction in heat-related relative risk through physiological adaptation will be insufficient to offset the climate change-driven escalation of future heat-related mortality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A Robust Cross-Sectional Assessment of the Impacts of COVID-19 Pandemic on the Prevalence of Female Genital Mutilation Among 0–14 Years Old Girls in Nigeria},

author = {Corentin Visée and Camille Morlighem and Chibuzor Christopher Nnanatu },

url = {https://doi.org/10.1177/17455057241311948},

year  = {2025},

date = {2025-05-26},

journal = {Women’s Health},

volume = {21},

abstract = {Female genital mutilation (FGM) is a human rights violation that still affects more than 3 million girls aged 0–14 years each year. To achieve the Sustainable Development Goal 2030 agenda, efforts have been made at the local, national and international levels to end the practice by the year 2030. However, the recent COVID-19 pandemic may have reversed the progress made due to increased rates of early marriage of girls, violence against children and school closures during lockdowns. Although some surveys have examined changes in FGM prevalence over the COVID-19 period, changes at the national and sub-national levels among 0–14 years old girls have not been quantified.



This study aimed to understand the potential impacts of the COVID-19 pandemic on the likelihood of FGM among girls aged 0–14 years, and whether it affected progress towards the elimination of FGM.



We used Bayesian hierarchical regression models implemented within the integrated nested Laplace approximations frameworks.



We modelled the likelihood and prevalence of FGM among girls aged 0–14 years before and after the COVID-19 pandemic in Nigeria, with respect to individual- and community-level characteristics, using Bayesian hierarchical models. We used the 2018 Demographic and Health Survey as the pre-COVID-19 period and the 2021 Multiple Indicator Cluster Survey as the post-COVID-19 period.



At the state level, FGM prevalence varied geographically and increased by 23% and 27% in the northwestern states of Katsina and Kana, respectively. There were 11% increase in Kwara and 14% increase in Oyo. However, at the national level, the prevalence of FGM was found to decrease from 19.5% to 12.3% between 2018 and 2021. Cultural factors were identified as the key drivers of FGM among 0–14 years old girls in Nigeria. The changes in the likelihood of girls undergoing FGM across the two time periods also varied across ethnic and religious groups following COVID-19 pandemic.



Our findings highlight that FGM is still a social norm in some states/regions and groups in Nigeria, thereby highlighting the need for a continued but accelerated FGM interventions throughout the country.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Beyond proximity: an observational study of stillbirth rates and emergency obstetric and newborn care accessibility in The Gambia},

author = {Oghenebrume Wariri and Winfred Dotse-Gborgbortsi and Schadrac C Agbla and Hawanatu Jah and Mamady Cham and Ba Foday Jawara and Mustapha Bittaye and Momodou T Nyassi and Musa Marena and Sainey Sanneh and Mariama Janneh and Beate Kampmann and Aduragbemi Banke-Thomas and Joy E Lawn and Uduak Okomo },

url = {https://doi.org/10.1136/bmjgh-2024-016579},

year  = {2025},

date = {2025-04-03},

journal = {BMJ Global Health},

abstract = {Stillbirths are disproportionately concentrated in sub-Saharan Africa, where geographical accessibility to basic/comprehensive emergency obstetric and newborn care (BEmONC and CEmONC) significantly influences maternal and perinatal outcomes. This study describes stillbirth rates within healthcare facilities in The Gambia and examines their distribution in relation to the geographical accessibility of these facilities.



We analysed 97 276 births recorded between 1 January 2013 and 31 December 2018, from 10 major public healthcare facilities in The Gambia. To standardise definitions, stillbirths were defined as fetal deaths with a birth weight of ≥500 g. Fresh stillbirths were reclassified as intrapartum, and macerated stillbirths were reclassified as antepartum. Linear regression with cubic splines was used to model trends, and AccessMod software estimated travel times to facilities.



Among recorded births, 5.1% (4873) were stillbirths, with an overall stillbirth rate of 51.3 per 1000 births (95% CI: 27.5 to 93.6). Intrapartum stillbirths accounted for 53.8% (27.6 per 1000 births; 95% CI: 14.4 to 49.8). Fully functional CEmONC facilities reported the highest stillbirth rates, including the National Teaching Hospital (101.7 per 1000 births, 95% CI: 96.8 to 106.8). Approximately 42.8%, 58.9% and 68.3% of women aged 15–49 lived within a 10, 20 and 30 min travel time, respectively, to fully functional CEmONC facilities, where high stillbirth rates were concentrated.



In The Gambia, intrapartum stillbirth rates remain alarmingly high, even in geographically accessible CEmONC facilities. Inadequate documentation of fetal heart rate on admission hampers accurate classification, complicating targeted interventions. Ensuring that EmONC-designated facilities—particularly those providing BEmONC services—are fully functional with essential equipment, trained staff and robust referral systems, while enhancing the timeliness and quality of obstetric care, is crucial to reducing stillbirth rates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A scoping review of the methods used to estimate health facility catchment populations for child health indicators in sub‑Saharan Africa},

author = {Matthew Johnson and Wole Ademola Adewole and Victor Alegana and C. Edson Utazi and Nuala McGrath and James Wright 

},

doi = {10.1186/s12963-025-00374-0},

year  = {2025},

date = {2025-03-03},

urldate = {2025-03-03},

journal = {Population Health Metrics},

volume = {23},

number = {11},

issue = {11},

abstract = {Evidence indicating persistent geographic inequalities in health outcomes signifies a need for routine subnational monitoring of health-related Sustainable Development Goal targets in sub-Saharan Africa. Health facilities may be an appropriate subnational unit for monitoring purposes, but a lack of suitable demographic data complicates the production of baseline facility-level population denominators against which progress can be reliably measured. This scoping review aimed to map the methods and data sources used to estimate health facility catchment areas and translate them to population denominators for child health indicators in the region.

Peer-reviewed research publications and grey literature reports were identified by searching bibliographic databases and relevant organisational websites. The inclusion criteria required that studies were conducted in sub-Saharan Africa since January 2000, described quantitative method(s) for estimating health facility catchment areas and/or population denominators, and focussed on children as the population of interest. Following title/abstract then full text screening of search results, relevant data were extracted using a standard form. Thematic analysis was undertaken to extract themes and present a narrative synthesis.

Overall, 33 research publications and 3 grey literature reports were included. Of these, only 7 research studies and 1 technical guidance document outlined aims explicitly framed around methods development and/or evaluation. Studies increasingly estimated catchment areas using complex geostatistical or travel time-based modelling approaches rather than simpler proximity metrics, and produced denominators by intersecting catchment boundaries with gridded population surfaces rather than aggregating area-based administrative counts. Few studies used data produced by or describing health facilities to link estimation methods to service utilisation patterns, inter-facility competition or facility characteristics.

There is a need for catchment population estimation methods that can be scaled to national-level facility networks and replicated across the region. This could be achieved by leveraging routinely collected health data and other readily available and nationally consistent data sources. Future methodological development should emphasise modern geostatistical approaches drawing upon the relative strengths of multiple data sources and capturing the range of spatial, supply-side, individual-level and environmental factors with potential to influence catchments’ extent, shape and demographic composition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Beyond physical accessibility, bypassing health facilities offering caesarean section: insights from women in Dakar’s slums },

author = {El Hadji Malick Sylla and Ndeye Awa Fall and Winfred Dotse-Gborgbortsi and Arsène Brunelle Sandie and Barrel Sow Gueye and Diarra Bousso Senghor and Birane Cissé and Fadima Yaya Bocoum and Ibrahima Ousmane Sy and Cheikh Faye},

doi = {10.1136/bmjopen-2024-088606},

year  = {2025},

date = {2025-02-14},

journal = {BMJ Open},

volume = {15},

abstract = {The study examines the geographic  accessibility of Comprehensive Emergency Obstetric Care (CEmONC) among women residing in the slums of Dakar.



Design: The study is a cross-sectional geographic analysis of caesarean care utilisation in health facilities offering the service in Dakar.



Setting: The study was conducted in urban slum areas in Dakar.



Participants: 763 women living in urban slums who had undergone a caesarean section in six health facilities in Dakar between July and December 2022.



Outcome measures: The proportion of women bypassing the nearest health facility and travel time to health facilities.



Key findings: show that most women in Dakar’s urban slums live within 5min from a health facility offering caesarean services, with an average travel time of 6.3min. However, 44.3% bypassed nearby facilities, often travelling outside their district. Medical referral was the primary reason for bypassing (43.2%), followed by the search for higher quality care (13.5%) and reliance on family or social networks (14.9%). Only a small proportion (1.4%) cited more affordable treatment costs as a reason for bypassing.



Conclusion: Despite the good geographical accessibility of health facilities offering caesarean sections in Dakar, many women bypass nearby facilities due to medical referrals and the search for higher quality care, resulting in increased travel time and costs. Strengthening the quality and capacity of local health centres in urban slums is crucial to minimising unnecessary bypassing and ensuring timely access to essential obstetric services.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{johnson2025scopingc,

title = {A scoping review of the methods used to estimate health facility catchment populations for child health indicators in sub-Saharan Africa},

author = {Matthew Johnson and Wole Ademola Adewole and Victor Alegana and C Edson Utazi and Nuala McGrath and James Wright},

year  = {2025},

date = {2025-01-01},

journal = {Population Health Metrics},

volume = {23},

number = {1},

pages = {1–37},

publisher = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{amouzou20252025,

title = {The 2025 report of the Lancet Countdown to 2030 for women's, children's, and adolescents' health: tracking progress on health and nutrition},

author = {Agbessi Amouzou and Aluisio J D Barros and Jennifer Requejo and Cheikh Faye and Nadia Akseer and Eran Bendavid and Cauane Blumenberg and Josephine Borghi and Sama El Baz and Frederik Federspiel and Leonardo Z Ferreira and Elizabeth Hazel and Sam Heft-Neal and Franciele Hellwig and Li Liu and Abdoulaye Maïga and Melinda Munos and Catherine Pitt and Yusra Ribhi Shawar and Jeremy Shiffman and Yvonne Tam and Neff Walker and Pierre Akilimali and Leontine Alkema and Paoli Behanzin and Peter Binyaruka and Zulfiqar Bhutta and Andrea Blanchard and Hannah Blencowe and Ellen Bradley and Nouria Brikci and Beatriz Caicedo-Velásquez and Anthony Costello and Winfred Dotse-Gborgbortsi and Shams El Arifeen and Majid Ezzati and Lynn P Freedman and Michel Guillot and Claudia Hanson and Rebecca Heidkamp and Luis Huicho and Chimaraoke Izugbara and Safia S Jiwani and Caroline Kabiru and Helen Kiarie and Mary Kinney and Fati Kirakoya-Samadoulougou and Joy Lawn and Nyovani Madise and Gouda Roland Mesmer Mady and Bruno Masquelier and Dessalegn Melesse and Kristine Nilsen and Jamie Perin and Usha Ram and Marina Romanello and Ghada E Saad and Sudha Sharma and Estelle M Sidze and Paul Spiegel and Hannah Tappis and Andrew J Tatem and and others},

doi = {10.1016/S0140-6736(25)00151-5},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {The Lancet},

volume = {405},

number = {10488},

issue = {10488},

pages = {1505–1554},

publisher = {Elsevier},

abstract = {In line with previous progress reports by Countdown to 2030 for Women's, Children's, and Adolescents' Health, this report analyses global and regional trends and inequalities in health determinants, survival, nutritional status, intervention coverage, and quality of care in reproductive, maternal, newborn, child and adolescent health (RMNCAH) and nutrition, as well as country health systems, policies, financing, and prioritisation. The focus is on low-income and middle-income countries (LMICs) where 99% of maternal deaths and 98% of child and adolescent deaths (individuals aged 0–19 years) occur, with special attention to sub-Saharan Africa and South Asia.

Recognising the urgency of reaching the Sustainable Development Goal (SDG) for health, SDG 3, and health-related targets by 2030, the report assesses whether the momentum needed to reach these goals has been sustained, accelerated, stagnated, or regressed in comparison with the Millennium Development Goal (MDG) period (2000–15). Although most health and health-related indicators continue to show progress, there has been a notable slowdown in the rate of improvement after 2015, falling well short of the pace needed to achieve the 2030 SDG targets. This deceleration in pace contrasts sharply with the aspired grand convergence in health, characterised by drastic reductions in mortality and RMNCAH inequalities, which was expected to occur during the SDG period based on the assumption that the spectacular progress achieved during the MDG period would continue unabated. Multiple threats, external and internal to the RMNCAH health community, must be addressed to safeguard the gains in RMNCAH and nutrition and to accelerate progress. Furthermore, a large gap between sub-Saharan Africa, especially West and Central Africa, and other parts of the world persists for many indicators, necessitating further prioritisation of this region.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{liu2025lessons,

title = {Lessons from failure to success on malaria elimination in the Huai River Basin in China},

author = {Xiaobo Liu and Pi Guo and Ying Liang and Chuanwei Chen and Jince Sun and Haisheng Wu and Tianyun Su and Shengjie Lai and Qiyong Liu},

url = {https://doi.org/10.1136/bmj-2024-080658},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {bmj},

volume = {389},

publisher = {British Medical Journal Publishing Group},

abstract = {Malaria is still a significant public health threat. After generations of control efforts, China was certified as a malaria-free country by the World Health Organization in June 2021. Not without its challenges, China’s experience of eliminating malaria is informative for elimination strategies in other countries and regions.

The Huai River Basin (HRB) in central China was the epicentre of two epidemics in the 1960s and 1970s, accounting for 93.1% and 91.2% of total reported cases in China, respectively.5 A comprehensive control strategy focused on eliminating infection sources, supplemented by integrated mosquito control, was adopted, such that by 1987 most regions in the HRB had achieved “basic malaria elimination”—with incidence rates below 1/10 000.

Unfortunately, malaria resurged in the HRB in 2003 and peaked in 2006. At that time, 62.45% of China’s total cases (60 193 cases) were in the HRB.5 As a result, the government’s leadership in malaria control was re-enforced through the implementation of comprehensive measures, such as mass drug administration, case management,6 and sustainable vector management.7 Consequently, the incidence of malaria in the HRB decreased significantly. No indigenous malaria has occurred in the HRB since the end of 2012.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{liu2025stratified,

title = {Stratified sustainable vector control strategies and measures for malaria control and elimination in China: a 70 year journey},

author = {Qiyong Liu and Yiguan Wang and Xiaobo Liu and Simon I Hay and Shengjie Lai},

url = {https://doi.org/10.1136/bmj-2024-080656},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {bmj},

volume = {389},

publisher = {British Medical Journal Publishing Group},

abstract = {Malaria is a mosquito-borne infectious disease that significantly threatens global health. Considerable efforts and investments have led to a steady decline in incidence and mortality over recent decades. However, 249 million cases were reported from 85 countries and areas in 2022, resulting in 608 000 deaths.1 Notably, approximately 95% of these cases and deaths occurred in the African region. China has had a heavy disease burden of malaria for more than 3000 years, evidenced by the Chinese character for malaria—疟 or nüè—discovered on oracle bone and bronze inscriptions from between 1562 and 1066 BC.2 Chinese medicine has historically been used to treat people with malaria. However, in the 1940s, before the foundation of the People’s Republic of China, the burden of malaria was still immense, with an estimated 30 million annual cases, more than 90% of the population at risk, and a fatality rate of approximately 1%.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{seidler2025subnational,

title = {Subnational variations in the quality of household survey data in sub-Saharan Africa},

author = {Valentin Seidler and Edson C Utazi and Amelia B Finaret and Sebastian Luckeneder and Gregor Zens and Maksym Bodarenko and Abigail W Smith and Sarah EK Bradley and Andrew J Tatem and Patrick Webb},

url = {https://doi.org/10.1038/s41467-025-58776-5},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Nature Communications},

volume = {16},

number = {1},

pages = {3771},

publisher = {Nature Publishing Group UK London},

abstract = {Nationally representative household surveys collect geocoded data that are vital to tackling health and other development challenges in sub-Saharan Africa. Scholars and practitioners generally assume uniform data quality but subnational variation of errors in household data has never been investigated at high spatial resolution. Here, we explore within-country variation in the quality of most recent household surveys for 35 African countries at 5 × 5 km resolution and district levels. Findings show a striking heterogeneity in the subnational distribution of sampling and measurement errors. Data quality degrades with greater distance from settlements, and missing data as well as imprecision of estimates add to quality problems that can result in vulnerable remote populations receiving less than optimal services and needed resources. Our easy-to-access geospatial estimates of survey data quality highlight the need to invest in better targeting of household surveys in remote areas.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chamberlain2025assessing,

title = {Assessing the impact of building footprint dataset choice for health programme planning: a case study of indoor residual spraying (IRS) in Zambia},

author = {Heather R Chamberlain and Derek Pollard and Anna Winters and Silvia Renn and Olena Borkovska and Chisenga Abel Musuka and Garikai Membele and Attila N Lazar and Andrew J Tatem},

url = {https://doi.org/10.1186/s12942-025-00398-7},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {International Journal of Health Geographics},

volume = {24},

number = {1},

pages = {13},

publisher = {Springer},

abstract = {The increasing availability globally of building footprint datasets has brought new opportunities to support a geographic approach to health programme planning. This is particularly acute in settings with high disease burdens but limited geospatial data available to support targeted planning. The comparability of building footprint datasets has recently started to be explored, but the impact of utilising a particular dataset in analyses to support decision making for health programme planning has not been studied. In this study, we quantify the impact of utilising four different building footprint datasets in analyses to support health programme planning, with an example of malaria vector control initiatives in Zambia.

Using the example of planning indoor residual spraying (IRS) campaigns in Zambia, we identify priority locations for deployment of this intervention based on criteria related to the area, proximity and counts of building footprints per settlement. We apply the same criteria to four different building footprint datasets and quantify the count and geographic variability in the priority settlements that are identified.

We show that nationally the count of potential priority settlements for IRS varies by over 230% with different building footprint datasets, considering a minimum threshold of 25 sprayable buildings per settlement. Differences are most pronounced for rural settlements, indicating that the choice of dataset may bias the selection to include or exclude settlements, and consequently population groups, in some areas.

The results of this study show that the choice of building footprint dataset can have a considerable impact on the potential settlements identified for IRS, in terms of (i) their location and count, and (ii) the count of building footprints within priority settlements. The choice of dataset potentially has substantial implications for campaign planning, implementation and coverage assessment. Given the magnitude of the differences observed, further work should more broadly assess the sensitivity of health programme planning metrics to different building footprint datasets, and across a range of geographic contexts and health campaign types.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nnanatu2025estimating,

title = {Estimating small area population from health intervention campaign surveys and partially observed settlement data},

author = {Chibuzor Christopher Nnanatu and Amy Bonnie and Josiah Joseph and Ortis Yankey and Duygu Cihan and Assane Gadiaga and Hal Voepel and Thomas Abbott and Heather R Chamberlain and Mercedita Tia and others},

url = {https://doi.org/10.1038/s41467-025-59862-4},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Nature Communications},

volume = {16},

number = {1},

pages = {4951},

publisher = {Nature Publishing Group UK London},

abstract = {Effective governance requires timely and reliable small area population counts. Geospatial modelling approaches which utilise bespoke microcensus surveys and satellite-derived settlement maps and other spatial datasets have been developed to fill population data gaps in countries where censuses are outdated and incomplete. However, logistics and costs of microcensus surveys and tree canopy or cloud cover obscuring settlements in satellite images limit its wider applications in tropical rural settings. Here, we present a two-step Bayesian hierarchical modelling approach that can integrate routinely collected health intervention campaign data and partially observed settlement data to produce reliable small area population estimates. Reductions in relative error rates were 32–73% in a simulation study, and ~32% when applied to malaria survey data in Papua New Guinea. The results highlight the value of demographic data routinely collected through health intervention campaigns or household surveys for improving small area population estimates, and how biases introduced by satellite data limitations can be overcome.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Multi-level determinants of timely routine childhood vaccinations in The Gambia: Findings from a nationwide analysis},

author = {Oghenebrume Wariri and Chigozie Edson Utazi and Uduak Okomo and Winfred Dotse-Gborgbortsi and Malick Sogur and Sidat Fofana and Kris A. Murray and Chris Grundy and Beate Kampmann },

url = {https://doi.org/10.1016/j.vaccine.2024.126500},

year  = {2025},

date = {2025-01-01},

journal = {Vaccine},

volume = {43},

abstract = {Achieving the ambitious goals of the Immunisation Agenda 2030 (IA2030) requires a deeper understanding of factors influencing under-vaccination, including timely vaccination. This study investigates the demand- and supply-side determinants influencing the timely uptake of key childhood vaccines scheduled throughout the first year of life in The Gambia.



We used two nationally-representative datasets: the 2019–20 Gambian Demographic and Health Survey and the 2019 national immunisation facility mapping. Using Bayesian multi-level binary logistic regression models, we identified key factors significantly associated with timely vaccination for five key vaccines: birth dose of hepatitis-B (HepB0), first, second, and third doses of the pentavalent vaccine (Penta1, Penta2, Penta3), and first-dose of measles-containing vaccine (MCV1) in children 



We found that demand-side factors, such as ethnicity, household wealth status, maternal education, maternal parity, and the duration of the household's residency in its current location, were the most common drivers of timely childhood vaccination. However, supply-side factors such as travel time to the nearest immunisation clinic, availability of cold-storage and staffing numbers in the nearest immunisation clinic were also significant determinants. Furthermore, the determinants varied across specific vaccines and the timing of doses. For example, delivery in a health facility (aOR = 1.58, 95 %CI: 1.02–2.53), living less than 30 min (aOR = 2.11, 95 %CI: 1.2–8.84) and living between 30 and 60 min (aOR = 3.68, 95 %CI: 1.1–14.99) from a fixed-immunisation clinic was associated with timely HepB0, a time-sensitive vaccine that must be administered within 24 h of birth. On the other hand, children who received Penta1 and Penta2 on time were three- to five-fold more likely to receive subsequent doses on time (Penta2 and Penta3, respectively). Finally, proximity to an immunisation facility with functional vaccine cold-storage was a significant supply-side determinant of timely MCV1 (aOR = 1.4, 95 %CI: 1.09–1.99).



These findings provide valuable insights for programme managers and policymakers. By prioritising interventions and allocating scarce resources based on these identified determinants, they can maximize their impact and ensure children in The Gambia receive timely vaccinations throughout their first year of life, contributing to IA2030 goals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmission},

author = {Natalya Kostandova and Catherine Schluth and Rohan Arambepola and Fatumah Atuhaire and Sophie Bérubé and Taylor Chin and Eimear Cleary and Oscar Cortes-Azuero and Bernardo García-Carreras and Kyra H. Grantz and Matt D. T. Hitchings and Angkana T. Huang and Nishant Kishore and Shengjie Lai and Soren L. Larsen and Stacie Loisate and Pamela Martinez and Hannah R. Meredith and Ritika Purbey and Tanjona Ramiadantsoa and Jonathan Read and Benjamin L. Rice and Lori Rosman and Nick Ruktanonchai and Henrik Salje and Kathryn L. Schaber and Andrew J. Tatem and Jasmine Wang and Derek A. T. Cummings and Amy Wesolowski },

url = {https://doi.org/10.1038/s41467-024-54895-7},

year  = {2024},

date = {2024-12-03},

journal = {Nature Communications},

volume = {15},

number = {10504},

abstract = {The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}