The national distribution of lymphatic filariasis cases in Malawi using patient mapping and geostatistical modelling

被引:2
|
作者
Barrett, Carrie [1 ]
Chiphwanya, John [2 ]
Mkwanda, Square [2 ]
Matipula, Dorothy E. [2 ]
Ndhlovu, Paul [2 ]
Chaponda, Limbikani [2 ]
Turner, Joseph D. [1 ]
Giorgi, Emanuele [3 ]
Betts, Hannah [1 ]
Martindale, Sarah [1 ]
Taylor, Mark J. [1 ]
Read, Jonathan M. [3 ]
Kelly-Hope, Louise A. [1 ,4 ]
机构
[1] Univ Liverpool Liverpool Sch Trop Med, Ctr Neglected Trop Dis, Dept Trop Dis Biol, Pembroke Pl, Liverpool, England
[2] Minist Hlth, Natl Lymphat Filariasis Eliminat Programme, Lilongwe, Malawi
[3] Lancaster Med Sch, Lancaster, England
[4] Univ Liverpool, Inst Infect Vet & Ecol Sci, Dept Livestock & Hlth 1, Liverpool, Lancs, England
来源
PLOS NEGLECTED TROPICAL DISEASES | 2024年 / 18卷 / 03期
基金
英国医学研究理事会;
关键词
LOWER SHIRE; INFECTION; DYNAMICS; DISTRICT;
D O I
10.1371/journal.pntd.0012056
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Background In 2020 the World Health Organization (WHO) declared that Malawi had successfully eliminated lymphatic filariasis (LF) as a public health problem. Understanding clinical case distributions at a national and sub-national level is important, so essential care packages can be provided to individuals living with LF symptoms. This study aimed to develop a national database and map of LF clinical case numbers across Malawi using geostatistical modelling approaches, programme-identified clinical cases, antigenaemia prevalence and climate information.Methodology LF clinical cases identified through programme house-to-house surveys across 90 sub-district administrative boundaries (Traditional Authority (TA)) and antigenaemia prevalence from 57 sampled villages in Malawi were used in a two-step geostatistical modelling process to predict LF clinical cases across all TAs of the country. First, we modelled antigenaemia prevalence in relation to climate covariates to predict nationwide antigenaemia prevalence. Second, we modelled clinical cases for unmapped TAs based on our antigenaemia prevalence spatial estimates.Principle findings The models estimated 20,938 (95% CrI 18,091 to 24,071) clinical cases in unmapped TAs (70.3%) in addition to the 8,856 (29.7%), programme-identified cases in mapped TAs. In total, the overall national number of LF clinical cases was estimated to be 29,794 (95% CrI 26,957 to 32,927). The antigenaemia prevalence and clinical case mapping and modelling found the highest burden of disease in Chikwawa and Nsanje districts in the Southern Region and Karonga district in the Northern Region of the country.Conclusions The models presented in this study have facilitated the development of the first national LF clinical case database and map in Malawi, the first endemic country in sub-Saharan Africa. It highlights the value of using existing LF antigenaemia prevalence and clinical case data together with modelling approaches to produce estimates that may be used for the WHO dossier requirements, to help target limited resources and implement long-term health strategies. Lymphatic filariasis (LF) is a disfiguring and painful Neglected Tropical Disease, transmitted by mosquitoes, and impairs affected individual's mental wellbeing, social participation, and ability to work. The two most common clinical manifestations are hydrocoele (scrotal swelling) and lymphoedema (swelling of the limbs). Estimates of LF clinical case numbers are required to provide national and local care needs assessment, and for elimination and surveillance purposes. Clinical case prevalence is currently not readily available or is unknown across many sub-Saharan African countries, however Malawi is unique as the LF Programme has conducted extensive house-to-house patient mapping activities across one third of the country. We used this clinical data in combination with measurements of LF infection prevalence and high-resolution climate information, to develop geostatistical models, which estimate the number of clinical cases in unmapped areas. This led to the development of a national database and map of clinical case estimates that will help the Malawi LF elimination programme to optimize limited resources, target morbidity management and disability prevention, and improve quality of life of the people affected by this disabling and disfiguring disease.
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页数:15
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