Epidemiology and case-control study of Lassa fever outbreak in Nigeria from 2018 to 2019

Ipadeola, Oladipupo; Furuse, Yuki; Ilori, Elsie; Dan-Nwafor, Chioma; Akabike, Kachikwulu O.; Ahumibe, Anthony; Ukponu, Winifred; Bakare, Lawal; Joseph, Gbenga; Saleh, Muhammad Muhammad; Muwanguzi, Esther Namukose; Olayinka, Adebola; Namara, Geoffrey; Naidoo, Dhamari; Iniobong, Akanimo; Amedu, Michael; Ugbogulu, Nkem; Makava, Favour; Adeoye, Olawunmi; Uzoho, Chukwuemeka; Anueyiagu, Chimezie; Okwor, Tochi; G, Nwando; Akano, Adejoke; Ogunniyi, Abiodun; Mohammed, Amina; Adeyemo, Ayodele; Ugochukwu, Dike K.; Agogo, Emmanuel; Ihekweazu, Chikwe

doi:10.1016/j.jinf.2019.12.020

Cited by 11 publications

(11 citation statements)

References 4 publications

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“…A total of 3063 participants recruited from 20 studies conducted in West Africa gave an overall fatality rate of 29.6% (95% CI; 22.3–37.5) ( Fig 2 ) [ 8 , 34 , 37 , 47 , 49 , 52 , 53 , 65 , 70 , 75 , 87 , 89 , 100 , 101 , 109 , 116 , 117 , 120 , 123 , 132 ]. All categories of participants with common, recent or old infections had relatively high case fatality rates ranging from 9.1 to 46.7%.…”

Section: Resultsmentioning

confidence: 99%

Systematic review and meta-analysis of the epidemiology of Lassa virus in humans, rodents and other mammals in sub-Saharan Africa

et al. 2020

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Accurate data on the Lassa virus (LASV) human case fatality rate (CFR) and the prevalence of LASV in humans, rodents and other mammals are needed for better planning of actions that will ultimately reduce the burden of LASV infection in sub-Saharan Africa. In this systematic review with meta-analysis, we searched PubMed, Scopus, Africa Journal Online, and African Index Medicus from 1969 to 2020 to obtain studies that reported enough data to calculate LASV infection CFR or prevalence. Study selection, data extraction, and risk of bias assessment were conducted independently. We extracted all measures of current, recent, and past infections with LASV. Prevalence and CFR estimates were pooled using a random-effect meta-analysis. Factors associated with CFR, prevalence, and sources of between-study heterogeneity were determined using subgroup and metaregression analyses. This review was registered with PROSPERO, CRD42020166465. We initially identified 1,399 records and finally retained 109 reports that contributed to 291 prevalence records from 25 countries. The overall CFR was 29.7% (22.3-37.5) in humans. Pooled prevalence of LASV infection was 8.7% (95% confidence interval: 6.8-10.8) in humans, 3.2% (1.9-4.6) in rodents, and 0.7% (0.0-2.3) in other mammals. Subgroup and metaregression analyses revealed a substantial statistical heterogeneity explained by higher prevalence in tissue organs, in case-control, in hospital outbreak, and surveys, in retrospective studies, in urban and hospital setting, in hospitalized patients, and in West African countries.

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Section: Resultsmentioning

confidence: 99%

Systematic review and meta-analysis of the epidemiology of Lassa virus in humans, rodents and other mammals in sub-Saharan Africa

et al. 2020

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“…While the change in fatality was 7.5% increment in Italy, it was 14.3% in Nigeria. Notwithstanding, the people's experience, the government, and the local public health officials' handling of the immediate past-Ebola outbreaks and ongoing monitoring of Lassa fever could have also played out [2,13,59].…”

Section: Discussionmentioning

confidence: 99%

“…It adversely affected communities and cities such as Conakry and Macenta (in Guinea); Kailahun, Kenema, Bombali, Port Loko, Western Rural and Western Urban (in Sierra Leone); Montserrado in Liberia, to mention but few [5,6], according to the Centers for Disease Control and Prevention [7,8]. However, as the country is scouting for strategies to attain the goals of sustainable development and Agenda 2063, in the face of fighting against incessant and highly reported serial killings, the communal conflicts, and herdsmenfarmers clashes [9][10][11][12], Lassa fever crept in [13]. Currently, the country is engulfed in a big fight for protection of lives under the mystifying coronavirus (COVID-19) that just reared up its ugly head [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Nigeria and Italy Divergences in Coronavirus Experience: Impact of Population Density

Amoo

Adekeye

Olawole-Isaac

et al. 2020

The Scientific World Journal

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Background. The reports and information on coronavirus are not conspicuously emphasising the possible impact of population density on the explanation of difference in rapid spread and fatality due to the disease and not much has been done on bicountry comparisons. Objective. The study examined the impact of population density on the spread of COVID-19 pandemic in two sociodemographic divergent countries. Methods. The study conducted a scoping review of published and unpublished articles including blogs on incidences and fatalities of COVID-19. The analysis followed qualitative description and quantitative presentation of the findings using only frequency distribution, percentages, and graphs. Results. The two countries shared similar experience of “importation” of COVID-19, but while different states ordered partial lockdown in Nigeria, it was an immediate total lockdown in Italy. The physician/patient ratio is high in Italy (1 : 328) but low in Nigeria (1 : 2500), while population density is 221 in Nigeria and 206 in Italy. Daily change in incidence rate reduced to below 20% after 51 and 30 days of COVID-19 first incidence in Italy and Nigeria, respectively. Fatality rate has plummeted to below 10% after the 66th day in Italy but has not been stabilised in Nigeria. Conclusion. The authors upheld both governments’ recommending measures that tilted towards personal hand-hygienic practices and social distancing. Authors suggested that if Italy with its high physician/patient ratio and lower population density compared to Nigeria could suffer high fatality from COVID-19 pandemic under four weeks, then Nigeria with its low physician/patient ratio and higher population density should prepare to face harder time if the pandemic persists.

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“…Temporal drivers of Lassa fever cases in high-incidence areas. A growing body of data from clinical records 5,18,20 , ethnographic and social science research 8,48 and rodent population and serological monitoring 49,50 suggests that LF risk may be climate-sensitive. Temporal trends in human and rodent infection are hypothesised to be associated with seasonal cycles in rodent population ecology, human land use and food storage practices 12 .…”

Section: Redding Et Al -Lassa Fever In Nigeriamentioning

confidence: 99%

“…Lassa virus (LASV; Arenaviridae, Order: Bunyavirales) is a WHO-listed priority pathogen and a major focus of international vaccine development funding 3 and, although often framed as a global health threat, LF is foremost a neglected endemic zoonosis. A significant majority of casesincluding those from recent years in Nigeria 4 are thought to arise directly from spillover from the LASV reservoir host, the widespread synanthropic rodent Mastomys natalensis, although with hospital-acquired infections potentially occurring in small clusters of human-to-human cases [5][6][7] . Risk factors for spillover, while not well understood, are thought to include factors that increase direct and indirect contact between rodents and people, including ineffective food storage, housing quality, and certain agricultural practices such as crop processing 8,9 .…”

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confidence: 99%

Spatiotemporal analysis of surveillance data enables climate-based forecasting of Lassa fever

Redding

Gibb

et al. 2020

Preprint

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Lassa fever (LF) is an acute rodent-borne viral haemorrhagic fever that is a longstanding public health concern in West Africa and increasingly a global health priority. Recent molecular studies1,2 have confirmed the fundamental role of the rodent host (Mastomys natalensis) in driving human infections, but LF control and prevention efforts remain hampered by a limited baseline understanding of the disease’s true incidence, geographical distribution and underlying drivers3. Here, through analysing 8 years of weekly case reports (2012-2019) from 774 local government authorities (LGAs) across Nigeria, we identify the socioecological correlates of LF incidence that together drive predictable, seasonal surges in cases. At the LGA-level, the spatial endemic area of LF is dictated by a combination of rainfall, poverty, agriculture, urbanisation and housing effects, although LF’s patchy distribution is also strongly impacted by reporting effort, suggesting that many infections are still going undetected. We show that spatial patterns of LF incidence within the endemic area, are principally dictated by housing quality, with poor-quality housing areas seeing more cases than expected. When examining the seasonal and inter-annual variation in incidence within known LF hotspots, climate dynamics and reporting effort together explain observed trends effectively (with 98% of observations falling within the 95% predictive interval), including the sharp uptick in 2018-19. Our models show the potential for forecasting LF incidence surges 1-2 months in advance, and provide a framework for developing an early-warning system for public health planning.

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Epidemiology and case-control study of Lassa fever outbreak in Nigeria from 2018 to 2019

Cited by 11 publications

References 4 publications

Systematic review and meta-analysis of the epidemiology of Lassa virus in humans, rodents and other mammals in sub-Saharan Africa

Systematic review and meta-analysis of the epidemiology of Lassa virus in humans, rodents and other mammals in sub-Saharan Africa

Nigeria and Italy Divergences in Coronavirus Experience: Impact of Population Density

Spatiotemporal analysis of surveillance data enables climate-based forecasting of Lassa fever

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