Descriptive epidemiology of Lassa fever, its trend, seasonality, and mortality predictors in Ebonyi State, South- East, Nigeria, 2018—2022 DOI Creative Commons

Adanna Ezenwa-Ahanene,

Adetokunbo Taophic Salawu,

Ayo Stephen Adebowale

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 18, 2024

Nigeria is an epicenter for Lassa fever. Ebonyi state located in the South-Eastern region of where a high burden fever has been reported. Therefore, this study was designed to assess epidemiology fever, its seasonality, trend, and mortality predictors state, South-East, Nigeria. We analyzed data extracted from State Integrated Disease Surveillance Response (IDSR) system over five years (2018–2022). A total 1578 reported cases were captured IDSR out which 300 laboratory-confirmed. Data using descriptive statistics, additive time series model, quadratic equation, logistic regression model (α0.05). Spatial distribution conducted Arc G.I.S. The mean age individuals with 29.4 ± 17.8 years. showed seasonal trend across provided best fit predicting cumulative (R2 = 98.4%, P-value < 0.05). Projected year 2023 123 1st quarter, 23 2nd 42 3rd 17 4th quarter. seasonality index + 70.76, -28.42, -9.09, -33.2 1st, 2nd, 3rd, quarters respectively. followed declining (slope -0.1363). Farmers 70% less likely die compared those not working (aOR:0.3, CI: 0.17–0.83). hot spots Abakaliki Ezza Local Government Areas. Although there disease pattern. Being farmer protective against risk dying While efforts eliminate mitigate spread should be strengthened, more attention target peak period disease.

Language: Английский

Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe DOI Open Access
Gerry A. Quinn, Michael Connolly, Norman Fenton

et al.

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(2), P. 334 - 334

Published: Jan. 6, 2024

Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined contribution of these three factors progression pandemic.

Language: Английский

Citations

7
Drivers of success in global health outcomes: A content analysis of Exemplar studies DOI Creative Commons
Nadia Akseer, David Phillips

PLOS Global Public Health, Journal Year: 2024, Volume and Issue: 4(5), P. e0003000 - e0003000

Published: May 9, 2024

Applying a positive outlier lens is one effective approach for generating evidence to inform global health policy, program, and funding decisions. Exemplars in Global Health (EGH) program that studies countries have made extraordinary progress outcomes (despite limited resources) disseminates their successes through multiple types of outputs. To date, EGH has studied, or studying, 14 topics 28 countries. This paper aims identify findings, summarized as themes sub-themes, appear among all completed studies. We developed conceptual framework used content analysis the top thematic areas drivers programmatic success across were between June 2020-May 2023. The (N = 31) spanned six including under-five child mortality (n 6), childhood stunting 5), community workers (CHW) 4), vaccine delivery 3), COVID-19 response newborn maternal reduction 7) 19 sub-Saharan Africa, Latin America, South Central Asia, Caribbean regions. Top defined those critical catalytic achieving intended outcome. Eight key identified: (1) efficient data collection use decision-making, (2) strong political commitment leadership, (3) stakeholder coordination, (4) local, connected, capacitated workforce, (5) intentional women's empowerment engagement, (6) adoption implementation national policies, (7) sustainable financing, (8) equitable, outreach targeting. These cross-cutting span broad range development outcomes, sectors, populations, indicate need effectively integrate people, systems, sectors improve outcomes. Findings from this study aim support peer learning evidence-based decision-making funders, policymakers, other stakeholders.

Language: Английский

Citations

2
Seasonality of COVID-19 incidence in the United States DOI Creative Commons

El Hussain Shamsa,

Ali Shamsa,

Kezhong Zhang

et al.

Frontiers in Public Health, Journal Year: 2023, Volume and Issue: 11

Published: Dec. 5, 2023

Background The surges of Coronavirus Disease 2019 (COVID-19) appeared to follow a repeating pattern COVID-19 outbreaks regardless social distancing, mask mandates, and vaccination campaigns. Objectives This study aimed investigate the seasonality incidence in United States America (USA), delineate dominant frequencies periodic patterns disease. Methods We characterized periodicity incidences over first three full seasonal years (March 2020 March 2023) pandemic USA. utilized spectral analysis approach find naturally occurring oscillation data using Fast Fourier Transform (FFT) algorithm. Results Our revealed four peaks periodogram: two most show period 366 days 146.4 days, while smaller indicate periods 183 122 days. indicates that there is single outbreak occurs approximately once every year, which correlates with early/mid-winter months. 3 per year matches well each annual year. Conclusion predictable outbreaks, will guide public health preventative efforts control future outbreaks. However, methods used this cannot predict amplitudes outbreak: multifactorial problem involves complex environmental, social, viral strain variables.

Language: Английский

Citations

6
Trend and Descriptive Epidemiology of Lassa fever in Ebonyi State, 2018 - 2022 DOI Creative Commons

Adanna Ezenwa-Ahanene,

Adetokunbo Taophic Salawu,

Ayo Stephen Adebowale

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 28, 2024

Abstract Background Lassa fever’s emergence in Nigeria has been a public health concern over the years. Ebonyi state is located South-Eastern zone of where high burden Lassa fever reported. Assessment trend and risk factors for are yet to be fully explored state. We investigated descriptive epidemiology Fever state, South-East, Nigeria. Method This study was analysis data extracted from State Integrated Disease Surveillance Response (IDSR) system five-year period (2018-2022). A total 1578 reported cases captured IDSR out which 300 were laboratory-confirmed. The seasonality assessed using an additive time series model ascertain quarter year when disease expected at its peak. predicted identified fitted among linear, quadratic, cubic exponential models (α0.05). Results mean age individuals with 29.4 ± 17.8 showed seasonal across quadratic provided best fit predicting cumulative (R2 = 98.4%, P-value <0.05). Projected 2023 123 1st quarter, 23 2nd 42 3rd 17 4th quarter. index +70.76, -28.42, -9.09, -33.2 1st, 2nd, 3rd, quarters respectively. followed declining (slope= -0.1363). Farmers 70% less likely die compared those not working (aOR:0.3, CI: 0.17-0.83). Conclusion: Although the there period. Adequate preparedness mitigate spread during peak recommended.

Language: Английский

Citations

0
Descriptive epidemiology of Lassa fever, its trend, seasonality, and mortality predictors in Ebonyi State, South- East, Nigeria, 2018—2022 DOI Creative Commons

Adanna Ezenwa-Ahanene,

Adetokunbo Taophic Salawu,

Ayo Stephen Adebowale

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 18, 2024

Nigeria is an epicenter for Lassa fever. Ebonyi state located in the South-Eastern region of where a high burden fever has been reported. Therefore, this study was designed to assess epidemiology fever, its seasonality, trend, and mortality predictors state, South-East, Nigeria. We analyzed data extracted from State Integrated Disease Surveillance Response (IDSR) system over five years (2018–2022). A total 1578 reported cases were captured IDSR out which 300 laboratory-confirmed. Data using descriptive statistics, additive time series model, quadratic equation, logistic regression model (α0.05). Spatial distribution conducted Arc G.I.S. The mean age individuals with 29.4 ± 17.8 years. showed seasonal trend across provided best fit predicting cumulative (R2 = 98.4%, P-value < 0.05). Projected year 2023 123 1st quarter, 23 2nd 42 3rd 17 4th quarter. seasonality index + 70.76, -28.42, -9.09, -33.2 1st, 2nd, 3rd, quarters respectively. followed declining (slope -0.1363). Farmers 70% less likely die compared those not working (aOR:0.3, CI: 0.17–0.83). hot spots Abakaliki Ezza Local Government Areas. Although there disease pattern. Being farmer protective against risk dying While efforts eliminate mitigate spread should be strengthened, more attention target peak period disease.

Language: Английский

Citations

0