Anticipating visceral leishmaniasis epidemics due to the conflict in Northern Ethiopia
Notice bibliographique
Résumé
On November 4, 2020, conflict erupted between the Ethiopian federal government and the Northern Ethiopian regional forces called the Tigray People's Liberation Front [1,2].The crisis has since driven over 4 million people to flee their homes, often with little possessions and no shelter, remaining internally displaced in the Tigray, Afar, and Amhara regions known to be endemic for visceral leishmaniasis (VL) [1][2][3][4].The Internal Displacement Monitoring Centre estimates that this conflict triggered the "highest displacement figures ever recorded for any country in any given year" [2].An additional 59,000 people have sought safety in eastern Sudan, concentrated around Gedaref and southern Kassala states, also known to be highly endemic for VL [4,5].East Africa currently composes the global epicenter of VL, accounting for 66% of the reported cases worldwide [6].It also comprises the area with the highest rate of VL-HIV coinfection, further amplifying VL transmission [4,7].Considering that conflict has previously triggered large VL epidemics with elevated case fatality, additional funding and operational coordination for a regional approach to VL screening, treatment and prevention will be required for the WHO to reach its goal of eliminating this neglected tropical disease as a public health problem by 2030 [4,5,8,9].Visceral leishmaniasis is a vector-borne disease transmitted by sandflies [3,4].This systemic disease affects the reticuloendothelial system and is fatal if untreated [4].In East Africa, visceral leishmaniasis is caused by Leishmania donovani and is predominantly transmitted by the Phlebotomus orientalis sandflies that thrive in the Acacia-Balanites forests along Ethiopia's northwestern border with Sudan [3].Phlebotomus orientalis is exophagic, preferring to bite the human host outside the home [10].Thus, sleeping outdoors is a significant risk factor for VL, a factor that renders refugees without shelter particularly vulnerable to VL acquisition [9,10].Since VL in East Africa is principally understood to be anthroponotic, human migration acts as one of the primary drivers of disease transmission [4,9].Previous refugee crises have produced large deadly epidemics of VL in East Africa [5,8].Within a year of conflict breaking out in South Sudan in 2013, cases of VL more than tripled in the Jonglei and Upper Nile States [5].Earlier wars catalyzed devastating VL epidemics.After war exploded in South Sudan in 1983, approximately one third of the Western Upper Nile's population of 280,000 died of VL during a 10-year period [8].While conflict has long been known to trigger outbreaks of neglected tropical diseases, epidemics of VL are deemed to be the deadliest as conflict interferes with the provision of care for a fatal disease [5].Furthermore, human migration introduces VL to new locations outside those of known endemicity.This phenomenon is well documented among Ethiopian migrant laborers who descend from high-altitude Amhara areas to work on commercial farms on the Sudanese border [3].
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».