Mosquito Population Modification for Malaria Control

*Rebeca Carballar-Lejarazú, Taylor Tushar, Thai Binh Pham and Anthony James*

#### **Abstract**

Malaria is a mosquito-borne disease that kills millions of people every year. Existing control tools have been insufficient to eliminate the disease in many endemic regions and additional approaches are needed. Novel vector-control strategies using genetic engineering to create malaria-resistant mosquitoes (population modification) can potentially contribute a new set of tools for mosquito control. Here we review the current mosquito control strategies and the development of transgenic mosquitoes expressing anti-parasite effector genes, highlighting the recent improvements in mosquito genome editing with CRISPR-Cas9 as an efficient and adaptable tool for gene-drive systems to effectively spread these genes into mosquito populations.

**Keywords:** *Anopheles*, mosquito control, genetic manipulation, CRISPR/Cas9

#### **1. Introduction**

#### **1.1 Malaria and mosquito control**

Mosquitoes in the genus *Anopheles* transmit to humans the *Plasmodium* parasites that cause malaria. Malaria is one of the most devastating mosquito-borne diseases worldwide, affecting more than 225 million people yearly, especially in sub-Saharan Africa and India [1].

Interventions to control anophelines have been ongoing since Sir Ronald Ross's discovery of the complete malaria transmission cycle in the late nineteenth century. The first large-scale vector control interventions in the early twentieth century relied on management and control of anopheline breeding habitats via manipulation of the environment (**Figure 1**) [2]. However, the discovery and subsequent development of dichloro-diphenyl-trichloroethane (DDT) in the early 1940s led to a new era of vector control after successes with the insecticide by the U.S. Army in World War II and various field trials proved its powerful ability to control malaria [3]. The initial successes with DDT were so great that malaria eradication began to appear feasible to some malariologists, and in 1955, the World Health Assembly launched the Global Malaria Eradication Programme (GMEP) with a goal to assist nations in eradicating malaria by providing technical advice and consolidating the resources needed for large-scale eradication campaigns. The World Health Organization (WHO) Expert Committee

#### **Figure 1.**

*Timeline of vector-control approaches and outcomes. Important events and timepoints of malaria vector control efforts and progress in the perspective of obstacles and downturns. Although great progress was made through the history of malaria vector control, many natural and artificial challenges have hindered the goal of malaria eradication.*

on Malaria was responsible for designing the eradication campaign schedule, which consisted of four distinct phases: preparatory, attack, consolidation, and maintenance. Completion of the eradication schedule was estimated to require 8–10 years [4]. Despite previous observations of insecticide resistance to DDT in Greece in 1951, the attack phase relied almost exclusively on the use of indoor residual spraying (IRS) of this insecticide to reduce adult mosquito populations supplemented by chloroquine to treat infections [5]. Large reductions in malaria case incidence, morbidity and mortality were observed worldwide because of the GMEP campaign and malaria was eliminated in many countries with temperate climates (**Figure 2**) [6–10]. However, progress began to falter by the mid 1960s and some countries participating in the GMEP reverted from the consolidation phase back to the attack phase. Countries such as Sri Lanka, which was an exemplary model for GMEP successes, began to experience

*Mosquito Population Modification for Malaria Control DOI: http://dx.doi.org/10.5772/intechopen.104907*

**Figure 2.**

*Global estimated number of malaria deaths. Estimated malaria mortality declined significantly from 1920s to 1970s due to many malaria control efforts countrywide and internationally but slowed from 1970s to 2020. Sources [6–9].*

epidemic resurgences of malaria [11]. Additionally, resistance to DDT became widespread throughout the participating countries. By the late 1960s, political and financial support for the GMEP had waned and the aim for eradication within a finite timeline was replaced by the aim of controlling malaria within an indefinite timeline.

Control of malaria after the dissolution of the GMEP devolved to a country-bycountry basis. Some nations that had benefited from participation in the GMEP continued to make progress in reducing the burden of malaria. However, most African nations were never included in the GMEP, and without dedicated resources, financial support or personnel trained in vector control techniques, the continent continued to suffer greatly as population growth paralleled an increase in malaria morbidity and mortality. In 1975 the WHO estimated that over one million infants and children were dying annually due to malaria in sub-Saharan Africa [12]. A systemic analysis of global malaria mortality from 1980 to 2010 estimated a peak of malaria deaths occurred in 2004 with over 1.8 million deaths occurring globally [13]. By the beginning of the second millennium, the rapid expansion of disease burden due to the absence of a global strategy and lack of unified political will became soberingly evident in the global malaria mortality rates.

The combination of skyrocketing malaria mortality and philanthropic interests of the world's ultra-wealthy led to a renewed interest and consolidation of financial and political will for advances in malaria control and elimination at the beginning of the second millennium. The formation of the Roll Back Malaria Partnership (RBM) and creation of the United Nations Millennium Development Goals helped to solidify a new global strategy. After years of disparate global malaria control without clearly-defined metrics to track progress, the renewed enthusiasm ushered in a return to specific targets and strategies reminiscent of what was attempted in the 1950s with the GMEP. The new global malaria programme (GMP) had the benefit of additional vector control tools such as a wider variety of insecticide products for IRS and insecticide-treated nets (ITN). The new program also benefited from the historical perspectives of renown

malariologists on the causes leading to the failures of the original eradication effort. The UN development goals included Target 6.C with a stated aim "to have halted by 2015 and begun to reverse the incidence of malaria and other major diseases" (UN Millennium goals [14]) and the RBM created a Global Malaria Action Plan, which outlined an overarching strategy and system of support needed to achieve malaria eradication [15]. The enhanced frameworks for combating malaria also were accompanied by increased funding in the formation of the Global Fund to Fight AIDS, Tuberculosis and Malaria and the US President's Malaria Initiative [16]. The renewed efforts and consolidation of strategies and finances in the early 2000s proved successful, and Target 6.C of the development goals was achieved. There was a 30% reduction in global incidence and 47% decline in mortality due to malaria from 2001 to 2015 [1]. Continuing the momentum of the progress made in the early millennium, WHO member states created and adopted a new global technical strategy (GTS) in 2015 and set an ambitious new target for a 90% reduction in global malaria burden by 2030 [17].

The WHO and RBM developed a new framework of strategies and guidelines to meet the ambitious 2030 targets. The first pillar of the WHO's post-2015 GTS called for expansions of access. Firstly, it called for expanded access to vector control using either IRS or long-lasting insecticide treated nets (LLINs) and secondly, it called for expanded access to chemoprevention and treatment, especially in vulnerable groups such as children and pregnant women. The new guidelines also highlighted the importance of generating entomological and epidemiological surveillance data to guide vector control and diseasetreatment efforts and advised that accumulation of these data should be considered an intervention in itself. While supporting elements of the post-2015 GTS encouraged advancements in research and new technology, these were secondary to the ramp-up of coverage using existing vector control and treatment technologies. Unfortunately, despite the restructured objectives and continual commitment to malaria elimination by global parties in 2015, progress in reducing malaria morbidity and mortality has slowed or stalled in many mid- to high-transmission countries. The post-2015 GTS set an interim goal of achieving 40% reductions in malaria case incidence and mortality by 2020, however, the case incidence at that time had only decreased by 3% and mortality decreased by 22% compared to 2015 levels [17].

#### **1.2 Current challenges of vector control**

Many factors contribute to the decreased rate of reducing malaria incidence and mortality rates. Population growth in malaria-endemic countries has substantially increased the at-risk population. Initial modeling efforts completed during the creation of the post-2015 GTS predicted that with the existing vector control tools and treatment options available, coverage would have to exceed 80% of high-risk populations to reduce the malaria burden [17]. However, growing populations combined with continuing instabilities of governments, natural disasters, conflicts, and epidemics have hampered the ability to reach this needed intervention coverage. As a result, there has been inadequate access to available vector control interventions. It is estimated that only 46% of the population at risk for malaria is protected by an insecticide-treated net and the percent of at-risk population covered by IRS is only 2.4%, a 2.9% decrease when compared to 2010 coverage [1].

In addition to problems of access, the existing vector control interventions face problems of reduced efficacy due to the widespread emergence of insecticide resistance in the major anopheline vectors. Resistance in the form of either target-site insensitivity or metabolomic changes has been observed for all classes of insecticides

#### *Mosquito Population Modification for Malaria Control DOI: http://dx.doi.org/10.5772/intechopen.104907*

currently being used to treat bed nets or in IRS campaigns [18]. Cuticular or penetration resistance has also been observed [19], which also reduces the impact of bed nets and IRS campaigns. As of 2020, only eight of the 82 malaria-endemic countries reported no resistance to all classes of insecticides. Resistance to pyrethroids, the only insecticide approved to treat bed nets, is widespread and resistance was reported in just under 70% of the locations that performed WHO approved standardized testing [1]. The varied resistance mechanisms and wide geographical spread of resistance imposes a major threat to the objectives of the GTS, yet no vector control products based on a new class of insecticide have been introduced to global markets since pyrethroids were introduced in the 1970s however, several have been re-purposed for their use in bed-nets and IRS and new formulations are under development with the World Health Organization Pesticide Evaluation Scheme [20, 21]. An additional challenge to current vector control tactics is behavioral resistance of the mosquito vectors. The long-term use of ITN and IRS creates a selective pressure that has been shown to result in behavioral and population compositional changes of malaria-vectoring species over time [22]. Changes in *An. gambiae* spp., the primary vector species of sub-Saharan Africa, to bite earlier in the day and outdoors (exophilic) have been observed [23, 24]. Changes in population structure to favor exophilic and day-biting malaria vectors such as *An. funestus* also have been implicated in areas where residual transmission of malaria occurs despite good ITN or IRS coverage [25].

An increase in access to vector control interventions to above 80% coverage of at-risk populations will likely lead to a reduction in case incidence and mortality but may not result in the desired 90% reduction of malaria burdens due to the challenges presented by resistance. With no new classes of insecticide approved for the control of malaria, widespread insecticide resistance and evidence of behavioral changes perpetuating residual transmission, the limitations of the current GTS vector control initiatives are obvious. New tools and technologies are needed urgently to meet the 2030 targets of the GTS. Ideally, novel vector control strategies should be cost-effective and sustainable as well as implementable and maintainable in a variety of regions irrespective of changes in government stability, conflicts or catastrophes. Population modification using genetic techniques to confer parasite refractoriness in mosquitoes is one such novel strategy that could greatly aid in achieving the ambitious goals of the GMP.


**1. Introduction**

Amongst renewable energy technologies the current trend is technology which aims to optimally utilize clean and sustainable energy sources, based on current and future economic and societal needs. Social and economic development is always followed with an increase in energy demand. Currently, most of the energy demand is fulfilled by nonrenewable fossil fuels, including natural gas, coal, and petroleum. The formation of fossil fuels took hundreds of million years. It is predicted that with the current consumption rate, fossil fuel will deplete in the near future [1,2]. Furthermore, the burning of fossil fuels results in negative environmental impacts, such as global warming, acid rain, climate change, and others. Hence, it is crucial to look for alternative energy resources that are clean and sustainable to replace the non-renewable fossil fuel.

There are a series of studies that have been done in exploring renewable energy technologies, such as solar energy, wind energy, tidal energy, and biofuels [3–8]. Among the available renewable energy, liquid biofuel from biomass resources has received a lot of attention [9–11], especially in the transportation sector, as it offers an opportunity to replace petroleum in operating the combustion engine with little to no modification [12,13]. In fact, over 90% of transportation nowadays is still dependent on non-renewable fossil fuel [14]. Therefore, many works have been done to enhance and improve the biofuel production

**Citation:** Ong, M.Y.; Nomanbhay, S.; Kusumo, F.; Raja Shahruzzaman, R.M.H.; Shamsuddin, A.H. Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN). *Energies* **2021**, *14*, 295. https://doi.org/10.3390/ en14020295

Received: 15 December 2020 Accepted: 5 January 2021 Published: 7 January 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

technologies, especially biodiesel, a renewable replacement of diesel fuel [15–18]. Nevertheless, there is only a little information about the production of bio-kerosene (bio-jet fuel). Bio-jet fuel is a promising alternative fuel for a jet engine. Other than the aviation sector, bio-jet fuel also can be used in the power generation sector to operate the gas turbine engine. Hence, the bio-jet fuel production technologies should be further explored and investigated in obtaining a comparable renewable replacement for petroleum-based kerosene at sufficient volume.

Based on the statistical report, flights produced 859 Mt of carbon dioxide (CO2) globally in 2017. In the other words, approximately 2% of the CO2 emitted through human activities is contributed by the global aviation sector. In addition, this 859 Mt of CO2 is responsible for 12% of CO2 emission from all transports sources [19,20]. CO2 is one of the greenhouse gases that will trap heat within the Earth's atmosphere, causing global warming and climate change. In order to mitigate the CO2 emissions from air transport and, at the same time, to address the global challenge of climate change, the International Air Transport Association (IATA) has adopted a set of targets and approaches. One of the ambitious targets is to achieve 50% reduction in net aviation carbon emissions by 2050 as compared to 2005, through the deployment of sustainable low-carbon fuels, such as bio-jet fuel [19].

Generally, aviation liquid fuel can be produced from different biomass feedstock with different methods [21–23]. Currently, transesterification and hydrotreating are the main production method of bio-jet fuel [24]. Unlike the hydrotreating process, transesterification requires an upgrading process to separate bio-jet fuel from the product of transesterification (biodiesel). Although an additional downstream process is required, however, the transesterification process operates under milder condition as compared to the hydrotreating process. Hence, its operating cost are relatively lower. The transesterification process involves three consecutive and reversible reactions (refer to Equations (1)–(3)) that react triglyceride with alcohol in the presence or absence of a catalyst and produce a mixture of fatty acid alkyl ester (FAAE or biodiesel) and glycerol as a by-product. In overall, transesterification requires 1 mole of triglyceride and 3 moles of alcohol to produce 3 moles of biodiesel, as shown in Equation (4). However, practically, the excess amount of alcohol is usually used to shift the equilibrium to the product side and allow the phase separation of biodiesel from the glycerol [25].

*Triglyceride* (*oil or f at*) + *ROH* (*alcohol*) ↔ *Diglyceride* + *RCOOR* (1)

*Diglyceride* + *ROH* ↔ *Monoglyceride* + *RCOOR* (2)

$$\text{Monoglyceride} + \text{ROH} \leftrightarrow \text{Glycerol} + \text{R\prime} \text{COOR} \tag{3}$$

#### *Triglyceride* (*oil or f at*) + 3*ROH* (*alcohol*) ↔ *Glycerol* + 3*R COOR* (*FAAE*) (4)

Commonly, methanol is used for biodiesel production via transesterification reactions. This is because methanol is cheaper, allows phase separation to be conducted more easily, and permits the transesterification process to be conducted under milder conditions [26]. However, methanol is very toxic to humans, as in the body methanol is metabolized into formaldehyde and then formic acid. Therefore, there is the scope of using ethanol for producing biodiesel. Ethanol has several advantages to methanol, such as offering better solvent properties and low toxicity relative to methanol [27,28] Furthermore, there is a study reported that the biodiesel formed using ethanol, the fatty acid ethyl ester (FAEE) present a higher cetane number, calorific value, oxidation stability, lubricant characteristics, lower cloud and pour points, and also have lower tailpipe emissions in comparison to the product collected using methanol, fatty acid methyl ester (FAME) [29,30].

In addition, microwave technology is deployed to replace conventional heating in this study. Microwave technology is a green processing method that offers several advantages, such as by being more environmental-friendly, in terms of lower energy consumption. Furthermore, the volumetric heating mechanism of microwave heating also allows rapid heating, enhances chemical reaction rate and selectivity, and improves the production quality and yield [25]. Microwave heating has received a lot of attention since the 1970s, especially in the chemical research. Conventional heating transfers heat into the reactant through the reactant vessel via conduction and convection (wall heating). However, microwave heating is highly dependent on the dielectric properties of the reactant [25,31]. It allows direct heating of the material without heat-up of the reactant vessel [32]. Hence, microwave heating allows selective and rapid heating, as mentioned previously.

Numerous studies have been done on the microwave-assisted transesterification process for biodiesel production [25,33,34]. Compared to other approaches, transesterification is the simplest and a widely-accepted method to reduce oil viscosity because it is costeffective. Therefore, modeling the process and optimizing the process input variables involved are important in order to save time, achieve high product yield and reduce the overall cost to produce biodiesel. Response surface methodology (RSM) and artificial neural network (ANN) are one of the mathematical methods for modeling transesterification processes [35–38]. Some of the advantages that RSM has are the durability under optimal setting conditions and the ability to minimize the number of trials required to provide sufficient evidence for statistically acceptable results [37].

Artificial neural network (ANN) is an information processing system that has characteristics such as biological neural networks that imitates the behaviour and learning process of the human brain. An interesting characteristic of this ANN is its ability to learn (learning and training). The training process at ANN aims to find convergent weights between layers so that the weights obtained to produce the desired output. ANNs are universal approximators and their predictions are based on prior available data, have shown great ability in solving complex nonlinear systems [39].

Ant colony optimization (ACO) is a swarm intelligence technique which is inspired by natural metaphors, namely communication and cooperation between ants to find the shortest path from the nest ants to the food. It is desirable to integrate ACO with ANN model since ACO is capable of optimizing complex process parameters [15,40]. Coupling ACO with the ANN is desirable since the ACO algorithm is capable of optimizing complex process parameters [41].

This study proposed the production of bio-jet fuel through microwave-assisted catalytic transesterification from coconut oil. Coconut oil was selected as the raw feedstock as it consists of a high percentage of medium-chain triglycerides, which made it suitable to be used for bio-jet fuel production [22,42]. An optimization study was conducted in this work based on three parameters, including oil to ethanol molar ratio, reaction time and microwave power, using response surface methodology (RSM) and artificial neural network (ANN) coupled with ant colony optimization (ACO) algorithm. Additionally, the relevant characterizations of coconut oil through the application of gas chromatographicmass spectrometry and Fourier transform infrared spectrometry analyses of the coconut oil, FAEE, and bio-jet fuel were conducted and reported. The physicochemical properties of the bio-jet fuel collected and their comparison with the ASTM standard are also reported in this paper.


3.1.5. Challenges Faced

Common difficulties in implementing CHOC's simulation program included time allocation, turnover of trained staff, and achieving the desired number of simulation sessions per month. There were several competing projects in the unit that made it difficult for the facilitators to allocate time for the goal number of sessions per month. This also made the growth of the team difficult to achieve. High census during October through December 2019 limited the team's ability to continue with a goal number of simulation sessions. Monthly webinars and face to face meetings helped CHOC's team trouble shoot some of these hurdles.