Policy and Prevention

**133**

**Chapter 9**

**Abstract**

Elimination

machine learning, COVID-19

**1. Introduction**

New Challenges in Malaria

In recent years, efforts to eliminate malaria has gained a tremendous momentum, and many countries have achieved this goal — but it has faced many challenges. Recent COVID-19 pandemic has compounded the challenges due to cessation of many on-field operations. Accordingly, the World Health Organization (WHO) has advocated to all malaria-endemic countries to continue the malaria elimination operations following the renewed protocols. The recent reports of artemisinin resistance in *Plasmodium falciparum* followed by indication of chloroquine resistance in *P. vivax*, and reduced susceptibility of synthetic pyrethroids used in long lasting insecticide nets are some issues hindering the elimination efforts. Moreover, long distance night migration of vector mosquitoes in sub-Saharan Africa and invasion of Asian vector *Anopheles stephensi* in many countries including Africa and Southeast Asia have added to the problems. In addition, deletion of histidine rich protein 2 and 3 (*Pfhrp2/3*) genes in *P. falciparum* in many countries has opened new vistas to be addressed for point-of-care diagnosis of this parasite. It is needed to revisit the strategies adopted by those countries have made malaria elimination possible even in difficult situations. Strengthening surveillance and larval source management are the main strategies for successful elimination of malaria. New technologies like Aptamar, and artificial intelligence and machine learning would prove very useful in addressing many ongoing issues related to malaria elimination.

**Keywords:** Malaria, *Plasmodium vivax*, *P. falciparum*, drug resistance, vector invasion, night migration, insecticide resistance, gene deletions,

surveillance, larval source management, elimination, Aptamar, Artificial intelligence,

In the past two decades, tremendous progress has been made in the fight against

malaria. A great deal of new knowledge on malaria parasite [1], insights in vector biology and control have helped target interventions resulting in substantial transmission reduction globally [2–4]. In 2019, World Health Organization (WHO) estimated 229 million malaria cases and 409,000 deaths in 87 malaria-endemic countries with large concentration of the total malaria burden (94%) in Africa [5]. Global malaria cases declined by 27% between 2000 and 2015, and only 2% between 2015 and 2019 indicating the slow progress rate in this period (**Figure 1**) [5]. Of the 29 countries that contributed 95% of the global malaria cases, Nigeria alone accounted for the highest at 27% followed by Democratic Republic of the Congo (12%), Uganda (5%), Mozambique (4%) and Niger (3%). A compiled data of global malaria cases

*Susanta Kumar Ghosh and Chaitali Ghosh*

#### **Chapter 9**
