ORCID Profile
0000-0002-5128-3288
Current Organisations
Telethon Kids Institute
,
UiT Norges arktiske universitet
,
KEMRI-Wellcome Trust Research Programme Nairobi
,
Drugs For Neglected Diseases Initiative (DNDi)
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Publications
Improving access to care and community health in Haiti with optimized community health worker placement
Publisher: Public Library of Science (PLoS)
Date: 10-05-2022
DOI: 10.1371/JOURNAL.PGPH.0000167
Abstract: The national deployment of polyvalent community health workers (CHWs) is a constitutive part of the strategy initiated by the Ministry of Health to accelerate efforts towards universal health coverage in Haiti. Its implementation requires the planning of future recruitment and deployment activities for which mathematical modelling tools can provide useful support by exploring optimised placement scenarios based on access to care and population distribution. We combined existing gridded estimates of population and travel times with optimisation methods to derive theoretical CHW geographical placement scenarios including constraints on walking time and the number of people served per CHW. Four national-scale scenarios that align with total numbers of existing CHWs and that ensure that the walking time for each CHW does not exceed a predefined threshold are compared. The first scenario accounts for population distribution in rural and urban areas only, while the other three also incorporate in different ways the proximity of existing health centres. Comparing these scenarios to the current distribution, insufficient number of CHWs is systematically identified in several departments and gaps in access to health care are identified within all departments. These results highlight current suboptimal distribution of CHWs and emphasize the need to consider an optimal (re-)allocation.
Spatiotemporal mapping of malaria prevalence in Madagascar using routine surveillance and health survey data
Publisher: Springer Science and Business Media LLC
Date: 22-10-2020
DOI: 10.1038/S41598-020-75189-0
Abstract: Malaria transmission in Madagascar is highly heterogeneous, exhibiting spatial, seasonal and long-term trends. Previous efforts to map malaria risk in Madagascar used prevalence data from Malaria Indicator Surveys. These cross-sectional surveys, conducted during the high transmission season most recently in 2013 and 2016, provide nationally representative prevalence data but cover relatively short time frames. Conversely, monthly case data are collected at health facilities but suffer from biases, including incomplete reporting and low rates of treatment seeking. We combined survey and case data to make monthly maps of prevalence between 2013 and 2016. Health facility catchment populations were estimated to produce incidence rates from the case data. Smoothed incidence surfaces, environmental and socioeconomic covariates, and survey data informed a Bayesian prevalence model, in which a flexible incidence-to-prevalence relationship was learned. Modelled spatial trends were consistent over time, with highest prevalence in the coastal regions and low prevalence in the highlands and desert south. Prevalence was lowest in 2014 and peaked in 2015 and seasonality was widely observed, including in some lower transmission regions. These trends highlight the utility of monthly prevalence estimates over the four year period. By combining survey and case data using this two-step modelling approach, we were able to take advantage of the relative strengths of each metric while accounting for potential bias in the case data. Similar modelling approaches combining large datasets of different malaria metrics may be applicable across sub-Saharan Africa.
The malaria transition on the Arabian Peninsula: progress toward a malaria-free region between 1960-2010.
Publisher: Elsevier
Date: 2013
A geo-coded inventory of anophelines in the Afrotropical Region south of the Sahara: 1898-2016
Publisher: F1000 Research Ltd
Date: 26-07-2017
DOI: 10.12688/WELLCOMEOPENRES.12187.1
Abstract: Background : Understanding the distribution of anopheline vectors of malaria is an important prelude to the design of national malaria control and elimination programmes. A single, geo-coded continental inventory of anophelines using all available published and unpublished data has not been undertaken since the 1960s. Methods : We have searched African, European and World Health Organization archives to identify unpublished reports on anopheline surveys in 48 sub-Saharan Africa countries. This search was supplemented by identification of reports that formed part of post-graduate theses, conference abstracts, regional insecticide resistance databases and more traditional bibliographic searches of peer-reviewed literature. Finally, a check was made against two recent repositories of dominant malaria vector species locations ( circa 2,500). Each report was used to extract information on the survey dates, village locations (geo-coded to provide a longitude and latitude), s ling methods, species identification methods and all anopheline species found present during the survey. Survey records were collapsed to a single site over time. Results : The search strategy took years and resulted in 13,331 unique, geo-coded survey locations of anopheline vector occurrence between 1898 and 2016. A total of 12,204 (92%) sites reported the presence of 10 dominant vector species/sibling species 4,473 (37%) of these sites were s led since 2005. 4,442 (33%) sites reported at least one of 13 possible secondary vector species 1,107 (25%) of these sites were s led since 2005. Distributions of dominant and secondary vectors conform to previous descriptions of the ecological ranges of these vectors. Conclusion : We have assembled the largest ever geo-coded database of anophelines in Africa, representing a legacy dataset for future updating and identification of knowledge gaps at national levels. The geo-coded database is available on Harvard Dataverse as a reference source for African national malaria control programmes planning their future control and elimination strategies.
Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa from 2000-2020
Publisher: Springer Science and Business Media LLC
Date: 11-06-2021
DOI: 10.1038/S41467-021-23707-7
Abstract: Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. The primary driving factors behind these findings are most likely strong cultural and social messaging around the importance of net use, low physical net durability, and a mixture of inherent commodity distribution challenges and less-than-optimal net allocation policies, respectively. These results can inform both policy decisions and downstream malaria analyses.
Global maps of travel time to healthcare facilities
Publisher: Springer Science and Business Media LLC
Date: 28-09-2020
Maps and Metrics of Insecticide-Treated Net Coverage in Africa: Access, Use, and Nets-Per-Capita, 2000-2020
Publisher: Research Square Platform LLC
Date: 16-02-2021
DOI: 10.21203/RS.3.RS-199628/V1
Abstract: Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. These results can inform both policy decisions and downstream malaria analyses.
Guidelines for the use and interpretation of assays for monitoring autophagy
Publisher: Informa UK Limited
Date: 04-2012
DOI: 10.4161/AUTO.19496
The prevalence of Plasmodium falciparum in sub-Saharan Africa since 1900.
Publisher: Springer Science and Business Media LLC
Date: 10-2017
DOI: 10.1038/NATURE24059
Mapping malaria by sharing spatial information between incidence and prevalence datasets
Publisher: Cold Spring Harbor Laboratory
Date: 17-02-2020
DOI: 10.1101/2020.02.14.20023069
Abstract: As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low prevalence areas are increasingly needed. For low burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in areas with both routine surveillance data and prevalence surveys, models that make use of the spatial information from prevalence point-surveys have great potential. Using case studies in Indonesia, Senegal and Madagascar, we compare two methods for incorporating point-level, spatial information into disaggregation regression models. The first simply fits a Gaussian random field to prevalence point-surveys to create a new covariate. The second is a multi-likelihood model that is fitted jointly to prevalence point-surveys and polygon incidence data. We find that the simple model generally performs better than a baseline disaggregation model while the joint model performance was mixed. More generally, our results demonstrate that combining these types of data improves estimates of malaria incidence.
Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case data
Publisher: eLife Sciences Publications, Ltd
Date: 06-2021
DOI: 10.7554/ELIFE.62122
Abstract: Towards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a c aign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts from 771 health facilities reporting from across the country throughout the 6-year period from January 2014 to December 2019. To this end, a novel hierarchical Bayesian modelling framework was developed in which a latent, pixel-level incidence surface with spatio-temporal innovations is linked to the observed case data via a flexible catchment sub-model designed to account for the absence of data on case household locations. These maps have focussed the delivery of indoor residual spraying and focal mass drug administration in the Grand’Anse Department in South-Western Haiti.
Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis
Publisher: Elsevier BV
Date: 2021
Detecting local risk factors for residual malaria in northern Ghana using Bayesian model averaging.
Publisher: Springer Science and Business Media LLC
Date: 29-09-2018
Spatial heterogeneity can undermine the effectiveness of country-wide test and treat policy for malaria: a case study from Burkina Faso.
Publisher: Springer Science and Business Media LLC
Date: 19-10-2016
Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana
Publisher: Springer Science and Business Media LLC
Date: 15-03-2019
Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia
Publisher: BMJ
Date: 02-2022
DOI: 10.1136/BMJGH-2021-007599
Abstract: HIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia. HIV, TB and malaria data were obtained from different nationwide prevalence surveys, and geospatial covariates were obtained from publicly available sources. A Bayesian model-based geostatistical framework was applied to each survey leveraging the strength of high-resolution spatial covariates to predict continuous disease-specific prevalence surfaces and their codistribution. The national prevalence was 1.54% (95% CI 1.40 to 1.70) for HIV, 0.39% (95% CI 0.34 to 0.45) for TB and 1.1% (95%CI 0.95 to 1.32) for malaria. Substantial subnational variation was predicted with the highest HIV prevalence estimated in Gambela (4.52%), Addis Ababa (3.52%) and Dire Dawa (2.67%) regions. TB prevalence was highest in Dire Dawa (0.96%) and Gambela (0.88%), while malaria was highest in Gambela (6.1%) and Benishangul-Gumuz (3.8%). Spatial overlap of their prevalence was observed in some parts of the country, mainly Gambela region. Spatial distribution of the diseases was significantly associated with healthcare access, demographic, and climatic factors. The national distribution of HIV, TB and malaria was highly focal in Ethiopia, with substantial variation at subnational and local levels. Spatial distribution of the diseases was significantly associated with healthcare access, demographic and climatic factors. Spatial overlap of HIV, TB and malaria prevalence was observed in some parts of the country. Integrated control programmes for these diseases should be targeted to these areas with high levels of co-endemicity.
Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicated Plasmodium falciparum malaria 1991–2019
Publisher: Springer Science and Business Media LLC
Date: 20-10-2020
DOI: 10.1186/S12936-020-03446-8
Abstract: Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an in idual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use its influence on malaria burden varies through space and time. This study uses data from 232 efficacy trials comprised of 86,776 infected in iduals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3–75.8), 70.1% (43.6–76.0) and 71.8% (46.9–76.4) for the 1991–2000, 2006–2010, and 2016–2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9–74.9) for 1991–2000 and 55.5% (27.1–73.4) for 2011–2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries’ treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.
Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)
Publisher: Informa UK Limited
Date: 02-01-2016
The changing limits and incidence of malaria in Africa: 1939-2009.
Publisher: Elsevier
Date: 2012
Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.
Publisher: Springer Science and Business Media LLC
Date: 04-11-2015
Related Organisations
University Of Oxford, Big Data Institute
Location: United Kingdom of Great Britain and Northern Ireland
Imperial College London
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Punam Amratia.