| Literature DB >> 32245445 |
Kelly Osezele Elimian1,2, Somto Mezue3, Anwar Musah4, Oyeronke Oyebanji5, Ibrahima Soce Fall6, Sebastian Yennan5, Michel Yao6, Patrick Okumu Abok6, Nanpring Williams5, Lynda Haj Omar6, Thieno Balde6, Kobina Ampah7, Ifeanyi Okudo7, Luka Ibrahim7, Arisekola Jinadu5, Wondimagegnehu Alemu7, Clement Peter7, Chikwe Ihekweazu5.
Abstract
BACKGROUND: The 2018 cholera outbreak in Nigeria affected over half of the states in the country, and was characterised by high attack and case fatality rates. The country continues to record cholera cases and related deaths to date. However, there is a dearth of evidence on context-specific drivers and their operational mechanisms in mediating recurrent cholera transmission in Nigeria. This study therefore aimed to fill this important research gap, with a view to informing the design and implementation of appropriate preventive and control measures.Entities:
Keywords: Cholera; Drivers; Multi-sectoral; Scoping review; Transmission
Mesh:
Year: 2020 PMID: 32245445 PMCID: PMC7118857 DOI: 10.1186/s12889-020-08521-y
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Fig. 1A flowchart showing the selection of documents for the scoping review
Baseline characteristics of reviewed documents (N = 45)
| Academic institution | 22 (48.89) |
| Academic and government | 7 (15.56) |
| Academic and hospital | 1 (2.22) |
| Academic and International NGO | 1 (2.22) |
| Governmental health institution | 12 (26.67) |
| Governmental health institution and International NGO | 1 (2.22) |
| International NGO | 1 (2.22) |
| Conference proceeding | 5 (11.11) |
| Peer-reviewed journal | 40 (88.89) |
| < 1990 | 4 (8.89) |
| 1990–2000 | 6 (13.33) |
| 2001–2010 | 6 (13.33) |
| 2011–2018 | 29 (64.44) |
| Akwa-Ibom and Cross-River | 1 (2.22) |
| Bauchi | 1 (2.22) |
| Bauchi and Gombe | 1 (2.22) |
| Bauchi, Borno and Gombe | 2 (4.44) |
| Bauchi, Borno and Osun | 1 (2.22) |
| Benue | 1 (2.22) |
| Borno | 2 (4.44) |
| Cross-River | 4 (8.89) |
| Jigawa | 2 (4.44) |
| Kaduna | 4 (8.89) |
| Kano | 2 (4.44) |
| Katsina | 1 (2.22) |
| Lagos | 2 (4.44) |
| Nasarawa | 1 (2.22) |
| Niger | 1 (2.22) |
| Ogun | 1 (2.22) |
| Osun | 2 (4.44) |
| Oyo | 7 (15.56) |
| Rivers | 1 (2.22) |
| Multiple states (> 3 states) | 8 (17.78) |
| Epidemic | 29 (64.44) |
| Endemic | 9 (20.00) |
| Endemic and epidemic | 6 (13.33) |
| Unspecified | 1 (2.22) |
| Prospective | 18 (40.00) |
| Retrospective | 23 (51.11) |
| Prospective and retrospective | 3 (6.67) |
| Unclear | 1 (2.22) |
| Case-control | 10 (22.22) |
| Cross-sectional | 28 (62.22) |
| Review | 4 (8.89) |
| Unspecified | 3 (6.67) |
| 329 (109–1220) | |
| All age groups | 17 (37.78) |
| Adults | 2 (4.44) |
| Children under-5 years | 1 (2.22) |
| Children under-14 years | 1 (2.22) |
| Unspecified | 24 (53.33) |
| Unspecified | 41 (91.11) |
| Yes | 4 (8.89) |
| Unspecified | 34 (75.56) |
| Yes | 11 (24.44) |
| Record extraction | 4 (8.89) |
| Microbiological examination | 7 (15.56) |
| Questionnaire | 9 (20.00) |
| Record extraction and microbiological examination | 1 (2.22) |
| Questionnaire and microbiological examination | 9 (20.00) |
| Record extraction and questionnaire | 2 (4.44) |
| Record extraction, questionnaire and microbiological examination | 1 (2.22) |
| Record extraction, questionnaire and observation | 2 (4.44) |
| Unspecified | 10 (22.22) |
| No | 23 (51.11) |
| Yes | 22 (48.89) |
| 6.53 (3.90) | |
| No | 40 (88.89) |
| Yes | 5 (11.11) |
| Community | 11 (24.44) |
| IDP camp | 1 (2.22) |
| Primary | 1 (2.22) |
| Secondary | 1 (2.22) |
| Tertiary | 4 (8.89) |
| Primary and secondary | 1 (2.22) |
| Secondary and tertiary | 3 (6.67) |
| Tertiary and private | 1 (2.22) |
| Unspecified health facility | 2 (4.44) |
| Unspecified health facility and community | 4 (8.89) |
| Unspecified health facility and IDP camp | 1 (2.22) |
| Unspecified | 15 (33.33) |
| No | 11 (24.44) |
| Yes | 22 (48.89) |
| Unspecified | 12 (26.67) |
| No | 40 (88.89) |
| Yes | 5 (11.11) |
| Classical | 1 (2.22) |
| El-Tor | 4 (8.89) |
| Classical & El-Tor | 2 (4.44) |
| Atypical El-Tor | 1 (2.22) |
| Unspecified | 37 (82.22) |
| O1 | 13 (28.89) |
| Non-O1 | 2 (4.44) |
| Unspecified | 30 (66.67) |
| Ogawa | 8 (17.78) |
| Inaba | 1 (2.22) |
| Ogawa and Inaba | 1 (2.22) |
| Unspecified | 35 (77.78) |
a Based on 34 out of 45 documents
bBased on 22 out of 45 documents
Fig. 2A map of Nigeria showing the 36 states and Federal Capital Territory. Source: Risk Communication Unit of the Nigeria Centre for Disease Control; developed using ArcGIS software version 10.7
Distribution of the drivers of cholera transmission in Nigeria, N = 45
| Social (demographic, cultural and economic) | 35 |
| Biological (host and genetics) | 3 |
| Environmental and climatic | 11 |
| Health systems-related | 8 |
| Multiplea | 27 |
aClimatic and social drivers (n = 2); social and biological drivers (n = 3); social and health systems-related drivers (n = 1); and two or more drivers (n = 21)
A description of the drivers of cholera transmission in Nigeria
| Social | Micro-level | |
| • Household | • Large household size and over-crowdedness • Poor sanitation and hygiene practices • Poor sewage disposal practices • Socioeconomic status (income and/or education) • Inter-family transmission/contact • Reliance on contaminated water sources (e.g. open wells) | |
| Micro-level | ||
| • Individual | • Open defecation • Consumption of seafood, sea and estuarine waters • Inadequate knowledge, and poor attitude and practices towards cholera • Religious beliefs (e.g. reluctance among female patients to seek care from male-dominated health providers) • Superstitious beliefs and/or myths | |
| Macro-level | ||
| • Governance/political | • Water scarcity due to inadequate power supply (electricity) • Inadequate public water supply | |
| Macro-level | ||
| • Trade and migration | • Increased fishing activities (e.g. trade traffic on the Calabar river estuary) • Increased migration and internal displacement of people (primarily due to armed conflicts) | |
| Biological | Genetics | • Acquisition of resistance genes • Changes in the major virulence determinant genes |
| Environmental and climatic | Environmental | |
| • Natural disaster | • Flooding | |
| Environmental | ||
| • Human-made | • Contaminated water sources by poor sewage disposal, waste dumps, abattoir, among others. • Street-vended and sachet water | |
| Climatic | • Unfavourable weather variables including rainfall and temperature | |
| Health systems-related | Health provision | • Inadequate funding for surveillance system • Inadequate training of health workers and health facilities • Inadequate supply of essential materials including oral cholera vaccine and oral rehydration solutions • Limited capacity for prompt and accurate cholera diagnosis, and delays in the notification of cholera cases |
| Health seeking | • Delay in seeking care at formal health facilities after cholera onset • Inadequate knowledge, attitude and practices towards cholera • | |
| Interphase between health provision and seeking | • Lack of trust by community members for formal health systems • Religious and/or superstitious beliefs | |
| Multiple | A combination of two or more drivers | • Over-crowdedness due to increasing population and natural disasters and human-made factors (e.g. conflicts) • Fragile surveillance system and limited political-will |
Fig. 3The dynamics of cholera drivers in Nigeria