A seasonal model to assess intervention strategies for preventing periodic recurrence of Lassa fever

Abstract

Lassa haemorrhagic fever is listed in WHO's Blueprint priority list of diseases and pathogens prioritized for research and development, affecting several hundreds of thousands of people each year. Lassa fever is spread via infected Natal multimammate mice and also through human-to-human contacts and it is a particular threat to pregnant women. Despite its importance, relatively few mathematical models have been established for modelling Lassa fever transmission up to now. We establish and study a new compartmental model for Lassa fever transmission including asymptomatic carriers, quarantine and periodic coefficients to model annual weather changes. We determine parameter values providing the best fit to data from Nigerian states Edo and Ondo from 2018–20. We perform uncertainty analysis and PRCC analysis to assess the importance of different parameters and numerical simulations to estimate the possible effects of control measures in eradicating the disease. The results suggest that the most important parameter which might be subject of control measures is death rate of mice, while mouse-to-human and human-to-human transmission rates also significantly influence the number of infected. However, decreasing the latter two parameters seems insufficient to eradicate the disease, while a parallel application of decreasing transmission rates and increasing mouse death rate might be able to stop the epidemic.

Epidemiological trends of Lassa fever in Nigeria, 2018–2021

“…The Lassa fever outbreaks appear to be more intense in the last quarter of the year through to the first quarter of the year after which cases continue to occur at a lower level for the rest of the year. This has been largely hypothesised to be the result of increased population of rodents due to more favourable condition for breeding towards the end of the rainy season and beginning of the dry season largely characterized by abundance of feeds on the farms [30][31][32][33]. The year-round reporting of cases further confirms the endemicity of Lassa fever in Nigeria and the need to focus on hitherto unrecognized endemic hotspots for optimised clinical evaluation, testing, confirmation, and treatment as well as the development and deployment of rapid diagnostic tests (RDTs) for routine evaluation of febrile illnesses.…”

The COVID-19 Impact on the Trends in Yellow Fever and Lassa Fever Infections in Nigeria

“…All infectious diseases require a specific set of health interventions in the reduction of their transmission, morbidity, and mortality and their impact on the health system at large. A study showed that the most effective measure for decreasing the spread of Lassa fever is an increase in the death rate of the rodents by mice culling which alternatively decreases the number of infected rodents (African rats), and even could drive the disease to complete extinction [ 42 ]. An additional measure is to reduce human-to-human transmission rates by increasing personal hygiene such as frequent handwashing, and the use of personal protective equipment (PPE) when caring for infected persons in the case of LF.…”

“…An additional measure is to reduce human-to-human transmission rates by increasing personal hygiene such as frequent handwashing, and the use of personal protective equipment (PPE) when caring for infected persons in the case of LF. Decreasing rodent-to-human transmission by using rodent-safe food containers and collecting garbage far from houses can assist in eradicating the disease [ 42 ].…”

Addressing the Lassa Fever Epidemic in West Africa: A Mathematical Modelling Approach

“…Considering Lassa fever epidemic is seasonal, usually in the dry season following the reproductive cycle of Mastomys spp. in rainy season (10), an innovative tool such as computational and mathematical modelling can help in predicting the accurate time and place to expect the outbreak, thereby allowing the necessary preventive and control measures to be put in place to prevent the outbreak. Unfortunately, despite the inclusion of Lassa Fever in the Blueprint list of priority diseases for research and development by the WHO in 2018 (11), only few mathematical modelling studies have been conducted on the disease compared to other infectious diseases (10) 14) analyzed the seasonal drivers of Lassa fever epidemics in Nigeria through mathematical models, which analyzed the datasets of human infection, rodent population, and climate change.…”

“…in rainy season (10), an innovative tool such as computational and mathematical modelling can help in predicting the accurate time and place to expect the outbreak, thereby allowing the necessary preventive and control measures to be put in place to prevent the outbreak. Unfortunately, despite the inclusion of Lassa Fever in the Blueprint list of priority diseases for research and development by the WHO in 2018 (11), only few mathematical modelling studies have been conducted on the disease compared to other infectious diseases (10) 14) analyzed the seasonal drivers of Lassa fever epidemics in Nigeria through mathematical models, which analyzed the datasets of human infection, rodent population, and climate change. Although these studies provide insights into different factors at play in Lassa fever transmission dynamics, no comprehensive mathematical modelling study has accurately predicted "where" and "when" to expect an outbreak, thereby limiting use of these studies to inform public health decisions (15).…”