Understanding Marburg Virus: Research and Implications

Infectious diseases can threaten health and safety worldwide. Since late 2019, when the SARS-CoV-2 virus appeared, we have seen other Outbreaks of new or returning diseases. Examples of these diseases include mpox, new types of hepatitis in children, Ebola, and Marburg virus disease (MVD). These cases show that we are still at risk from infectious diseases, which makes it essential to learn more about dangerous germs.

In 2018, an organization called the World Health Organization (WHO) made a list of nine germs that needed more research and development because they could cause large outbreaks. One of these is the Marburg virus (MV), a very deadly virus first identified in Germany and Serbia in 1967. Most outbreaks of MVD have happened in sub-Saharan Africa, including recent cases in Equatorial Guinea and Tanzania in 2023.

Fruit bats are the main carriers of the Marburg virus. People can get the virus by coming into direct contact with infected bats or other infected humans. Studies have shown that the virus can jump from bats to humans. The first known outbreak in humans was linked to African green monkeys. Symptoms of the disease can range from fever and headaches to severe bleeding, with a high risk of serious illness after infection.

Mathematical Models help us figure out how diseases spread and how to control them. These models can help public health officials make important decisions, such as planning for how many hospital beds might be needed and what types of actions could help stop an outbreak. However, gathering data for these models can take a long time, making it hard to respond quickly to outbreaks.

#Goals of the Review

To address these challenges, we wanted to review the existing research on designing quick models for tracking diseases like MVD. Our goal is to gather information about past outbreaks, modeling studies, and important details about how these diseases spread, how severe they can be, and other key factors like mutation rates and immunity in populations. By doing this, we aim to fill in knowledge gaps and create a helpful resource for future outbreaks from known or unknown diseases.

#Search Strategy and Study Selection

We searched for studies that discussed mathematical models and reported information about MVD. We focused on papers that detailed how the virus spreads, its severity, and previous outbreaks, published before March 31, 2023. After removing duplicates, we screened over 3,000 studies and selected 221 for full review. We further excluded studies that did not provide relevant data, resulting in 42 studies included in our final analysis.

#Data Extraction

Thirteen team members gathered information from these studies. They looked at details such as publication dates, quality, estimated parameters, and the specifics of past outbreaks. We only included information from outbreaks that were completed. We took note of key details such as numbers of cases and deaths to calculate the Case Fatality Ratio (CFR), which tells us how deadly the disease is.

Data was entered into a database, and we checked for quality using a structured assessment. For some papers, two reviewers worked together to ensure accuracy before finalizing the data.

#R Package Development

To make this information easy to access, we created an R package named epireview. This package contains data about MVD, allowing others to contribute new findings and keep the information updated.

#Data Analysis

The data we collected is presented in tables and figures. We aimed to show estimates of certain parameters, like the CFR, which indicates the percentage of deaths among those infected. We conducted two types of analyses for the CFR – one based on reported data and another from the outbreak data we collected.

We looked at various outbreaks through the lens of how they were connected. For instance, we considered an “outbreak” to be any situation where cases occurred in the same country during a specific time frame.

#Historical Overview of MVD Outbreaks

From our research, we found 13 studies detailing 23 MVD outbreaks. We identified seven distinct outbreaks, including the first ones in Germany and Yugoslavia, several in the Democratic Republic of the Congo, and various cases in Uganda and Angola. However, during our literature search, we could not find peer-reviewed studies on the 2023 outbreaks in Equatorial Guinea and Tanzania.

#Mathematical Models

We discovered that only one study had focused on modeling MVD transmission. This study used a specific type of mathematical model to assess how behavior changes could impact the number of cases and deaths. The model assumed that the virus spreads through direct human contact and that different groups of people might be affected differently.

#Epidemiological Parameters

We gathered a total of 71 parameter estimates, with seroprevalence being the most frequently reported. Other parameters included delays in seeking care, severity of illness, and mutation rates. Some studies reported on reproduction numbers, giving us insight into how rapidly the virus spreads.

#Case Fatality Ratio (CFR)

We found six estimates for the case fatality ratio, which ranged significantly across different outbreaks. The pooled estimates highlighted that the CFR can be quite high, suggesting that MVD is deadly. The high CFR and the characteristics of the virus indicate that it has the potential to cause significant problems in the regions where it occurs.

#Risk Factors

We also examined risk factors associated with MVD infection. Contact with confirmed cases was shown to be a significant risk factor for infection. Other factors included previous medical treatments and specific activities. Interestingly, gender did not appear to play a significant role in infection rates.

#Molecular Evolutionary Rates

Three studies reported on the rates at which the Marburg virus changes over time. This information is vital for understanding how the virus might adapt and spread.

#Quality Assessment

We assessed the quality of the studies we reviewed. We found that studies focusing on transmission parameters tended to score higher than those on seroprevalence. Over time, the overall quality of studies improved, which we believe reflects better research practices and greater transparency.

#Conclusion

This review offers a thorough examination of available research on MVD. Based on the studies, we noted that major outbreaks have been few and small compared to some other infectious diseases. The number of serious outbreaks reporting over 100 cases has been limited.

The information gathered here will help researchers create and refine models for MVD, allowing for better planning and management during future outbreaks. The R package epireview serves as a living resource, providing a straightforward way for scientists to update and share the latest findings.

It's crucial to keep exploring MVD, especially as new outbreaks occur. Collecting high-quality data during such events will be essential for understanding the disease and improving response strategies.

Encouragingly, this review points to the gaps in our knowledge and how filling these gaps will enhance our ability to manage MVD effectively in the future.